Claims:
1. A processor-implemented method (200) for determining optimal attachment points on a payload for transportation using multiple aerial vehicles, the method (200) comprising the steps of:
receiving, via one or more hardware processors, a number of the multiple aerial vehicles, and characteristics of the payload to be transported by the number of the multiple aerial vehicles, wherein the characteristics of the payload comprises: (i) a length of the payload, (ii) a total weight of the payload, and (iii) a center of gravity of the payload (202);
estimating, via the one or more hardware processors, a weight distribution of the payload, based on (i) the characteristics of the payload to be transported, and (ii) a weight distribution feasibility criteria, wherein the weight distribution of the payload comprises weights that are uniformly distributed along the payload (204);
virtually dividing, via the one or more hardware processors, the payload into a plurality of sub-payloads, wherein a number of divisions of the payload is greater than or equal to a product of (i) the length of the payload, and (ii) a predefined threshold (206);
identifying, via the one or more hardware processors, a possible attachment point from (i) each sub-payload of the plurality of sub-payloads, and (ii) each exterior end of the payload, to obtain a plurality of possible attachment points, wherein each possible attachment point from each sub-payload is indicative of a center point in the associated sub-payload (208);
obtaining, via the one or more hardware processors, an attachment point position for each possible attachment point by considering one exterior end of the payload as a starting position and other exterior end of the payload as an ending position, wherein the starting position represents a zero position and the ending position represents a maximum position which is equivalent to the length of the payload (210);
forming, via the one or more hardware processors, one or more possible attachment point sets, from the plurality of possible attachment points, based on a safety distance criteria associated with the aerial vehicles, using associated attachment point positions, wherein each possible attachment point set comprises one or more possible attachment points out of the plurality of possible attachment points (212);
determining, via the one or more hardware processors, a lift force for each possible attachment point present in each possible attachment point set of the one or more possible attachment point sets, based on the estimated weight distribution of the payload, using a slope deflection method (214);
determining, via the one or more hardware processors, a bending moment for each possible attachment point of the plurality of possible attachment points, based on the associated lift force and the estimated weight distribution of the payload (216);
determining, via the one or more hardware processors, (i) a differential lift force for each possible attachment point set of the one or more possible attachment point sets, based on the associated lift force for each of the one or more possible attachment points present in the associated possible attachment point set, and (ii) a mean separation distance for each possible attachment point set of the one or more possible attachment point sets, based on the attachment point position for each of the one or more possible attachment points present in the associated possible attachment point set (218);
obtaining, via the one or more hardware processors, a maximum absolute bending moment for each possible attachment point set of the one or more possible attachment point sets, by identifying the possible attachment point whose absolute bending moment is maximum and present across the one or more possible attachment points present in the corresponding possible attachment point set (220);
determining, via the one or more hardware processors, one or more optimal attachment point sets out of the one or more possible attachment point sets, based on a predefined feasibility criteria (222), wherein the predefined feasibility criteria comprises one of:
(A) determining if one possible attachment point set having a least differential lift force, is present, out of the one or more possible attachment point sets, and then classifying the possible attachment point set having the least differential lift force, as the optimal attachment point set; and
(B) determining if multiple possible attachment point sets having the same least differential lift force, are present, out of the one or more possible attachment point sets, and then:
(a) determining if one possible attachment point set having a least maximum absolute bending moment, is present, out of the multiple possible attachment point sets having the same least differential lift force, and then classifying the possible attachment point set having the least maximum absolute bending moment, as the optimal attachment point set; and
(b) determining if multiple possible attachment point sets having the same least maximum bending moment, are present, out of the multiple possible attachment point sets having the same least differential lift force, and then:
(i) determining if one possible attachment point set having a maximum mean separation distance, is present, out of the multiple possible attachment point sets having the same least maximum absolute bending moment, and then classifying the possible attachment point set having the maximum mean separation distance, as the optimal attachment point set; and
(ii) determining if multiple possible attachment point sets having the same maximum mean separation distance, are present, out of the multiple possible attachment point sets having the same least maximum absolute bending moment, and then classifying the multiple possible attachment point sets having the same maximum mean separation distance, as multiple optimal attachment point sets; and
classifying, via the one or more hardware processors, the one or more possible attachment points present in each of the one or more optimal attachment point sets, as one or more optimal attachment points (224).

2. The method as claimed in claim1, wherein the weight distribution feasibility criteria comprises: determining whether (i) a total weight of the estimated weight distribution of the payload is equal to the total weight of the payload, and (ii) the center of gravity of the estimated weight distribution depends on linearly varying weights between exterior ends of the payload.

3. The method as claimed in claim 1, wherein the number of the one or more possible attachment points present in each possible attachment point set is equivalent to the number of the aerial vehicles.

4. The method as claimed in claim 1, wherein determining the lift force for each possible attachment point present in each possible attachment point set of the one or more possible attachment point sets, based on the estimated weight distribution of the payload, using a slope deflection method, further comprising:
determining a fixed end bending moment at the associated possible attachment point, based on the weight distribution of each sub-payload corresponding to the associated possible attachment point;
determining a bending moment and a joint rotation angle at the associated possible attachment point, based on the associated fixed end bending moment, by using the slope deflection method;
calculating a section wise force for each sub-payload corresponding to the associated possible attachment point, based on the bending moment and the joint rotation angle at the associated possible attachment point; and
determining the lift force for the associated possible attachment point, based on the section wise force for each sub-payload corresponding to the associated possible attachment point.

5. A system (100) for determining optimal attachment points on a payload for transportation using multiple aerial vehicles, the system (100) comprising:
a memory (102) storing instructions;
one or more Input/Output (I/O) interfaces (106); and
one or more hardware processors (104) coupled to the memory (102) via the one or more I/O interfaces (106), wherein the one or more hardware processors (104) are configured by the instructions to:
receive a number of the multiple aerial vehicles, and characteristics of the payload to be transported by the number of the multiple aerial vehicles, wherein the characteristics of the payload comprises: (i) a length of the payload, (ii) a total weight of the payload, and (iii) a center of gravity of the payload;
estimate a weight distribution of the payload, based on (i) the characteristics of the payload to be transported, and (ii) a weight distribution feasibility criteria, wherein the weight distribution of the payload comprises weights that are uniformly distributed along the payload;
virtually divide the payload into a plurality of sub-payloads, wherein a number of divisions of the payload is greater than or equal to a product of (i) the length of the payload, and (ii) a predefined threshold;
identify a possible attachment point from (i) each sub-payload of the plurality of sub-payloads, and (ii) each exterior end of the payload, to obtain a plurality of possible attachment points, wherein each possible attachment point from each sub-payload is indicative of a center point in the associated sub-payload;
obtain an attachment point position for each possible attachment point by considering one exterior end of the payload as a starting position and other exterior end of the payload as an ending position, wherein the starting position represents a zero position and the ending position represents a maximum position which is equivalent to the length of the payload;
form one or more possible attachment point sets, from the plurality of possible attachment points, based on a safety distance criteria associated with the aerial vehicles, using associated attachment point positions, wherein each possible attachment point set comprises one or more possible attachment points out of the plurality of possible attachment points;
determine a lift force for each possible attachment point present in each possible attachment point set of the one or more possible attachment point sets, based on the estimated weight distribution of the payload, using a slope deflection method;
determine a bending moment for each possible attachment point of the plurality of possible attachment points, based on the associated lift force and the estimated weight distribution of the payload;
determine (i) a differential lift force for each possible attachment point set of the one or more possible attachment point sets, based on the associated lift force for each of the one or more possible attachment points present in the associated possible attachment point set, and (ii) a mean separation distance for each possible attachment point set of the one or more possible attachment point sets, based on the attachment point position for each of the one or more possible attachment points present in the associated possible attachment point set;
obtain a maximum absolute bending moment for each possible attachment point set of the one or more possible attachment point sets, by identifying the possible attachment point whose absolute bending moment is maximum and present across the one or more possible attachment points present in the corresponding possible attachment point set;
determine one or more optimal attachment point sets out of the one or more possible attachment point sets, based on a predefined feasibility criteria, wherein the predefined feasibility criteria comprises one of:
(A) determining if one possible attachment point set having a least differential lift force, is present, out of the one or more possible attachment point sets, and then classifying the possible attachment point set having the least differential lift force, as the optimal attachment point set; and
(B) determining if multiple possible attachment point sets having the same least differential lift force, are present, out of the one or more possible attachment point sets, and then:
(a) determining if one possible attachment point set having a least maximum absolute bending moment, is present, out of the multiple possible attachment point sets having the same least differential lift force, and then classifying the possible attachment point set having the least maximum absolute bending moment, as the optimal attachment point set; and
(b) determining if multiple possible attachment point sets having the same least maximum bending moment, are present, out of the multiple possible attachment point sets having the same least differential lift force, and then:
(i) determining if one possible attachment point set having a maximum mean separation distance, is present, out of the multiple possible attachment point sets having the same least maximum absolute bending moment, and then classifying the possible attachment point set having the maximum mean separation distance, as the optimal attachment point set; and
(ii) determining if multiple possible attachment point sets having the same maximum mean separation distance, are present, out of the multiple possible attachment point sets having the same least maximum absolute bending moment, and then classifying the multiple possible attachment point sets having the same maximum mean separation distance, as multiple optimal attachment point sets; and
classify the one or more possible attachment points present in each of the one or more optimal attachment point sets, as one or more optimal attachment points.

6. The system as claimed in claim 5, wherein the weight distribution feasibility criteria comprises: determining whether (i) a total weight of the estimated weight distribution of the payload is equal to the total weight of the payload, and (ii) the center of gravity of the estimated weight distribution depends on linearly varying weights between exterior ends of the payload.

7. The system as claimed in claim 5, wherein the number of the one or more possible attachment points present in each possible attachment point set is equivalent to the number of the aerial vehicles.

8. The system as claimed in claim 5, wherein the one or more hardware processors (104) are further configured to determine the lift force for each possible attachment point present in each possible attachment point set of the one or more possible attachment point sets, based on the estimated weight distribution of the payload, using a slope deflection method, by:
determining a fixed end bending moment at the associated possible attachment point, based on the weight distribution of each sub-payload corresponding to the associated possible attachment point;
determining a bending moment and a joint rotation angle at the associated possible attachment point, based on the associated fixed end bending moment, by using the slope deflection method;
calculating a section wise force for each sub-payload corresponding to the associated possible attachment point, based on the bending moment and the joint rotation angle at the associated possible attachment point; and
determining the lift force for the associated possible attachment point, based on the section wise force for each sub-payload corresponding to the associated possible attachment point.
, Description:FORM 2

THE PATENTS ACT, 1970
(39 of 1970)
&
THE PATENT RULES, 2003

COMPLETE SPECIFICATION
(See Section 10 and Rule 13)

Title of invention:
POWER GENERATION BY SUSPENSION SYSTEM TO CHARGE VEHICLE BATTERY

Applicant:
Tata Motors Limited
A company Incorporated in India under the Companies Act, 1956
Having address:
Bombay House, 24 Homi Mody Street,
Hutatma Chowk, Mumbai 400001,
Maharashtra, India

The following specification particularly describes the subject matter and the manner in which it is to be performed.
TECHNICAL FIELD
[001] The present invention relates to a power generating suspension system in vehicle, more specifically it is related to generating electrical energy by bump and rebound movement of damper body of vehicle suspension to charge vehicle battery.

BACKGROUND
[002] The MacPherson strut is a type of automotive suspension system that uses the top of a telescopic damper as the upper steering pivot. A MacPherson strut uses a wishbone, or a substantial compression link stabilized by a secondary link, which provides a mounting point for the hub carrier or axle of the wheel. This lower arm system provides both lateral and longitudinal location of the wheel. The upper part of the hub carrier is rigidly fixed to the bottom of the outer part of the strut proper; this slides up and down the inner part of it, which extends upwards directly to a mounting in the body shell of the vehicle.
[003] When vehicle is running over a road, all the road irregularities are taken care by the suspension system of vehicle by using spring and damper arrangement. Spring and damper are continuously moving up and down by means of road inputs. Traditional fossil fuel energy reserves are reducing day by day, and humanity is looking for clean energy sources. Therefore, use of electric vehicles is on rise but the limited infrastructure of charging stations is a concern. Vehicles currently in market have limited mileage available approx. 200-300 kilometers so there are limitations for usage of electric vehicles. With increase in battery capacity, range of vehicle can be increased but it is adding more cost to the customer. It is need of an hour to get more range (Mileage) with existing battery package by improving the battery charging by a secondary source other than the alternator.
OBJECTS OF THE INVENTION
[001] The main object of the invention is to generate power from auxiliary source to charge the vehicle battery.
[002] Another object of the invention is to generate power from auxiliary source to charge the vehicle battery to increase the mileage of electric vehicle.
[003] Yet another object of the invention is to generate power from damper / MacPherson strut to charge the vehicle battery.
[004] Yet another object of the invention is to use Faradays laws of magnetic induction to generate power by configuring magnet and coil around damper assembly.
[005] Yet another object of the invention is to provide alternate source of power to charge ageing battery of IC engine vehicle.
SUMMARY
[006] Before the present system and method are described, it is to be understood that this application is not limited to the particular machine or an apparatus, and methodologies described, as there can be multiple possible embodiments that are not expressly illustrated in the present disclosure. It is also to be understood that the terminology used in the description is for the purpose of describing the particular versions or embodiments only and is not intended to limit the scope of the present application. This summary is provided to introduce aspects related to a power generating suspension system to charge vehicle battery, and the aspects are further elaborated below in the detailed description.
[007] In one implementation, by using existing damper of suspension system power is produced by Faraday’s law of induction without affecting any suspension performance and without giving any additional load to the operation of suspension damper. Adding magnet and copper wire in damper arrangement of damper assembly results in power generation. The up and down movement of the damper body with magnet and stationary copper wire around dust cover leads to generation of electromagnetic field. This current is converted to DC current from AC current by using auxiliary alternator and directing the current to battery for charging and storage purpose. Battery charging is done continuously when vehicle is running on the road and mileage will be increased by 18-20%.
STATEMENT OF INVENTION
[008] Accordingly, the present invention discloses a power generation by suspension system in vehicle comprising of atleast one magnet configured to be mounted on striker cap of damper body, atleast one copper coil wounded around dust cover of said suspension and atleast one circuit to supply current generated by suspension assembly to charge vehicle battery.
[009] The electromagnetic field is configured to be induced by vertical movement of magnet within copper coil to charge vehicle battery. An auxiliary alternator is configured to be connected in the circuit to convert AC current generated by suspension system into DC current and supply to battery. A voltage regulator is configured to maintain the voltage between a predetermined range during charging of the vehicle battery. The current generated is configured to charge battery of electric vehicle and IC engine vehicle to increase mileage and life of battery. The suspension system is configured from a damper assembly. Magnet is configured to be molded on striker cap is a hollow cylindrical ring magnet and copper coil is configured to be of predetermined diameter and predetermined turn based on the size of suspension assembly.
BRIEF DESCRIPTION OF THE DRAWINGS
[0010] The foregoing summary, as well as the following detailed description of embodiment, is better understood when read in conjunction with the appended drawing. For the purpose of illustrating the disclosure, there is shown in the present document example constructions of the disclosure, however, the disclosure is not limited to the specific methods and apparatus disclosed in the document and the drawing.
[0011] The detailed description is described with reference to the accompanying figure. In the figure, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the drawing to refer like features and components.
[0012] Figure 1 (Prior Art) illustrates a vehicle suspension system.
[0013] Figure 2 (Prior Art) illustrates a sectional view of existing suspension damper.
[0014] Figure 3 illustrates a sectional view of power generating suspension damper with magnet and copper coils.
[0015] Figure 4 illustrates a damper assembly with magnet and copper coils wounded around dust cover.
[0016] Figure 5 illustrates a circuit diagram of power generating suspension damper.
[0017] Figures depicts various embodiments of the present disclosure for purpose of illustration only. Only skilled in the art will readily recognize from the following discussion that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles of the disclosure described herein.
DETAILED DESCRIPTION
[0018] Some embodiments of this disclosure, illustrating all its features, will now be discussed in detail. The words “comprising”, “having”, and “including,” and other forms thereof, are intended to be equivalent in meaning and be open ended in that an item or items following any one of these words is not meant to be an exhaustive listing of such item or items, or meant to be limited to only the listed item or items. Although any systems and methods similar or equivalent to those described herein can be used in the practice or testing of embodiments of the present disclosure, the exemplary, systems and methods are now described. The disclosed embodiments are merely exemplary of the disclosure, which may be embodied in various forms. .
[0019] Various modification to the embodiment will be readily apparent to those skilled in the art and the generic principles herein may be applied to another embodiment. However, one of ordinary skill in the art will readily recognize that the present disclosure is not intended to be limited to the embodiments illustrated but is to be accorded the widest scope consistent with the principles and features described herein..
[0020] The purpose of suspension system in vehicle is to keep vehicle on ground in all driving condition and absorb the shock which is created by road irregularities. The damper assembly suspension system consist of beam, damper, spring, top mount, bump stopper and dust cover. Springs in a suspension system helps to maintain the wheel contact with ground surface and thus supports ride and handling. Damper is an energy absorbing unit that absorbs the sudden jerks generated by a spring in a vehicle system. Top mount is a member which is getting connected in between body and suspension system and isolate the high frequency vibrations. Bump stopper is absorbing energy and which is released by spring and damper. Dust cover is preventing dust to go inside damper. When vehicle is going over a bump, wheel moves up and down in vehicle, damper is also moving up and down and there will be resistance from damper equal to damping force created by the valve and fluid inside damper arrangement. Striker cap will hit bump stopper when damper moves up in full bump condition.
[0021] The addition of two components like magnet and copper coil in suspension damper assembly is adapted to generate power for charging vehicle batteries. The bump and rebound movement of damper assembly allows vertical movement of magnet within the stationary copper coil wounded on dust cover. This movement of magnet within copper coil induces electromagnetic field according to Faradays law of induction. The current is converted to DC current from AC current by using alternator and directed to battery for charging and storage purpose. The power generating suspension damper ensures increase in mileage of electric vehicle and battery life of ageing battery of an IC engine vehicle.
[0022] A cylindrical ring magnet is molded on the plastic striker cap. Depending on magnetic strength requirements, thickness and length of magnet can be increased as packaging space is available. Accordingly, dust cover outer diameter can be increased as this dust cover is open to air without any packaging constrains. A clearance between the magnet and dust cover is optimally maintained for operation of damper system. Copper coil is wound over the dust cover through its entire surface area. Diameter of the copper coil is approximately 0.1mm. The coils are extended over the dust cover surface length of 180 to 200mm and the number of coils is with approximately 1500 turns.
[0023] Figure 1 shows a conventional vehicle suspension system comprising of wheel (10), damper (20) and spring (50). The suspension system in vehicle is to keep vehicle on ground in all driving condition and absorb the shock which is created by road irregularities. Springs in a suspension system helps to maintain the wheel contact with ground surface and thus supports ride and handling.
[0024] Figure 2 shows a conventional damper assembly comprising of bump stopper (22), striker cap (24), dust cover (26) and damper body (28). Bump stopper (22) is configured to absorb energy released by spring and damper. Dust cover (26) prevents entry of dust inside damper.
[0025] Figure 3 shows a damper assembly as per one embodiment of this invention used for power generation comprising of magnet (30), copper coil (32), top rubber mount bush (21), bump stopper (22) and damper body (28). A cylindrical ring magnet (30) is configured to be molded on the plastic striker cap (24). Depending on magnetic strength requirements and size of suspension the thickness and length of magnet (30) is varied. The clearance between the magnet and dust cover is optimally maintained for operation of damper assembly. Copper coils (32) are wounded over the dust cover through the entire surface area and diameter of the copper coil (32) is approximately 0.1mm. The coils are extended over the dust cover surface of length 180 to 200mm and number of coils is with 1500 turns. The bump and rebound movement of damper body (28) allows vertical movement of magnet (30) around the stationary copper coils wound on dust cover. Thus, the copper coils cuts the magnetic field during every single movement of the damper. By Faradays law of induced electricity, an EMF is induced in the system due to coils cutting the magnetic field at all instances. Induced EMF= N X ?F / ?? F: Magnetic Flux and T: Time. This induced EMF is used for charging the battery of vehicles.
[0026] Figure 4 shows a dust cover with copper coil (27) on a damper assembly. Copper coils are wounded over the dust cover through the entire surface area and diameter of the copper coil is approximately 0.1mm. The coils are extended over the dust cover surface of length 180 to 200mm and number of coils is with 1500 turns.
[0027] Figure 5 shows that in normal operating conditions rotor (64) rotates within stator (62) coils. Stator coils are connected to alternator for conversion of AC to DC current. This DC current passes through voltage regulator (60) and then supply to battery (70) and external voltage. In the case of voltage drop, voltage regulator signals rotor to increase RPM for producing more voltage generation and vice versa. Voltage produced by damper is connected to alternator, which is further connected to voltage regulator (60), to regulate the voltage in system and ensure constant voltage of 12V to 14V in system. After ageing of battery when there is a drop in generated voltage, the additional voltage generated from damper is used to increase battery life.
[0028] According to present subject matter, a power generation by suspension system in vehicle comprises; atleast one magnet (30) configured to be mounted on striker cap (24) of damper body (28), atleast one copper coil (32) wounded around dust cover (26) of said suspension, and atleast one circuit to supply current generated by suspension assembly to charge vehicle battery (70).
[0029] The electromagnetic field is configured to be induced by vertical movement of magnet (30) around copper coil (32) to charge vehicle battery (70).
[0030] An auxiliary alternator is configured to be connected in the circuit to convert AC current generated by suspension system into DC current and supply to battery (70).
[0031] A voltage regulator (60) is configured to maintain the voltage between a predetermined range during charging of the vehicle battery (70).
[0032] The current generated is configured to charge battery of electric vehicle and IC engine vehicle to increase mileage and life of battery.
FORM 2

THE PATENTS ACT, 1970
(39 of 1970)
&
THE PATENT RULES, 2003

COMPLETE SPECIFICATION
(See Section 10 and Rule 13)

Title of invention:
DETERMINING OPTIMAL ATTACHMENT POINTS ON PAYLOAD FOR TRANSPORTATION BY MULTIPLE AERIAL VEHICLES

Applicant:
Tata Consultancy Services Limited
A company Incorporated in India under the Companies Act, 1956
Having address:
Nirmal Building, 9th Floor,
Nariman Point, Mumbai 400021,
Maharashtra, India

The following specification particularly describes the invention and the manner in which it is to be performed.
TECHNICAL FIELD
[001] The disclosure herein generally relates to the field of payload transportation by aerial vehicles, and, more particularly, to methods and systems for determining optimal attachment points on a payload for transportation by multiple aerial vehicles.
BACKGROUND
[002] Aerial vehicles such as unmanned aerial vehicles (UAVs) are used to transport a payload from one target location to another target location, especially in warehouse management applications, time critical applications such as medicine and medical equipment support applications, remote applications where road transport is difficult, and so on. Each aerial vehicle has a limitation on the maximum weight of the payload that may carry. If the payload is heavy and large, where the weight of the payload exceeds the maximum capacity limit of a single aerial vehicle, then multiple aerial vehicles are required to lift and transport such large payloads. In the multiple aerial vehicles setup, each aerial vehicle may be connected at appropriate attachment point on the payload through cables for the transportation. However, determining the appropriate attachment points on the large payload to connect the multiple aerial vehicles, for achieving enhanced endurance, is a challenging problem. Further, the aerial vehicles typically use battery power for the overall operations and hence the consumption of battery power is very critical during the transportation.
[003] Conventional techniques in the art for transporting the large payload by multiple aerial vehicles are limited to control aspect of the payload transportation and trying to stabilize the multiple aerial vehicles by decreasing swing of the payload. Some conventional techniques choose random attachment points on the payload, by considering either a center of gravity (CG) of the payload or a CG of individual aerial vehicle. But if the load is attached randomly along any attachment point on the payload, then the weight transferred from the payload to each aerial vehicle may vary. As the weight supported by each aerial vehicle is different, the power consumed by each aerial vehicle may also be different. As a result, some of the aerial vehicles among the multiple aerial vehicles may consume more power as compared to others. The aerial vehicles that consume more power may dry more quickly as compared to the rest of the aerial vehicles and would affect the overall endurance of the multiple aerial vehicles.

SUMMARY
[004] Embodiments of the present disclosure present technological improvements as solutions to one or more of the above-mentioned technical problems recognized by the inventors in conventional systems.
[005] In an aspect, there is provided a processor-implemented method for determining optimal attachment points on a payload for transportation using multiple aerial vehicles, the method comprising the steps of: receiving a number of the multiple aerial vehicles, and characteristics of the payload to be transported by the number of the multiple aerial vehicles, wherein the characteristics of the payload comprises: (i) a length of the payload, (ii) a total weight of the payload, and (iii) a center of gravity of the payload; estimating a weight distribution of the payload, based on (i) the characteristics of the payload to be transported, and (ii) a weight distribution feasibility criteria, wherein the weight distribution of the payload comprises weights that are uniformly distributed along the payload; virtually dividing the payload into a plurality of sub-payloads, wherein a number of divisions of the payload is greater than or equal to a product of (i) the length of the payload, and (ii) a predefined threshold; identifying a possible attachment point from (i) each sub-payload of the plurality of sub-payloads, and (ii) each exterior end of the payload, to obtain a plurality of possible attachment points, wherein each possible attachment point from each sub-payload is indicative of a center point in the associated sub-payload; obtaining an attachment point position for each possible attachment point by considering one exterior end of the payload as a starting position and other exterior end of the payload as an ending position, wherein the starting position represents a zero position and the ending position represents a maximum position which is equivalent to the length of the payload; forming one or more possible attachment point sets, from the plurality of possible attachment points, based on a safety distance criteria associated with the aerial vehicles, using associated attachment point positions, wherein each possible attachment point set comprises one or more possible attachment points out of the plurality of possible attachment points; determining a lift force for each possible attachment point present in each possible attachment point set of the one or more possible attachment point sets, based on the estimated weight distribution of the payload, using a slope deflection method; determining a bending moment for each possible attachment point of the plurality of possible attachment points, based on the associated lift force and the estimated weight distribution of the payload; determining (i) a differential lift force for each possible attachment point set of the one or more possible attachment point sets, based on the associated lift force for each of the one or more possible attachment points present in the associated possible attachment point set, and (ii) a mean separation distance for each possible attachment point set of the one or more possible attachment point sets, based on the attachment point position for each of the one or more possible attachment points present in the associated possible attachment point set; obtaining a maximum absolute bending moment for each possible attachment point set of the one or more possible attachment point sets, by identifying the possible attachment point whose absolute bending moment is maximum and present across the one or more possible attachment points present in the corresponding possible attachment point set; determining one or more optimal attachment point sets out of the one or more possible attachment point sets, based on a predefined feasibility criteria, wherein the predefined feasibility criteria comprises one of: (A) determining if one possible attachment point set having a least differential lift force, is present, out of the one or more possible attachment point sets, and then classifying the possible attachment point set having the least differential lift force, as the optimal attachment point set; and (B) determining if multiple possible attachment point sets having the same least differential lift force, are present, out of the one or more possible attachment point sets, and then: (a) determining if one possible attachment point set having a least maximum absolute bending moment, is present, out of the multiple possible attachment point sets having the same least differential lift force, and then classifying the possible attachment point set having the least maximum absolute bending moment, as the optimal attachment point set; and (b) determining if multiple possible attachment point sets having the same least maximum bending moment, are present, out of the multiple possible attachment point sets having the same least differential lift force, and then: (i) determining if one possible attachment point set having a maximum mean separation distance, is present, out of the multiple possible attachment point sets having the same least maximum absolute bending moment, and then classifying the possible attachment point set having the maximum mean separation distance, as the optimal attachment point set; and (ii) determining if multiple possible attachment point sets having the same maximum mean separation distance, are present, out of the multiple possible attachment point sets having the same least maximum absolute bending moment, and then classifying the multiple possible attachment point sets having the same maximum mean separation distance, as multiple optimal attachment point sets; and classifying the one or more possible attachment points present in each of the one or more optimal attachment point sets, as one or more optimal attachment points.
[006] In another aspect, there is provided a system for determining optimal attachment points on a payload for transportation using multiple aerial vehicles, the system comprising: a memory storing instructions; one or more Input/Output (I/O) interfaces; and one or more hardware processors coupled to the memory via the one or more I/O interfaces, wherein the one or more hardware processors are configured by the instructions to: receive a number of the multiple aerial vehicles, and characteristics of the payload to be transported by the number of the multiple aerial vehicles, wherein the characteristics of the payload comprises: (i) a length of the payload, (ii) a total weight of the payload, and (iii) a center of gravity of the payload; estimate a weight distribution of the payload, based on (i) the characteristics of the payload to be transported, and (ii) a weight distribution feasibility criteria, wherein the weight distribution of the payload comprises weights that are uniformly distributed along the payload; virtually divide the payload into a plurality of sub-payloads, wherein a number of divisions of the payload is greater than or equal to a product of (i) the length of the payload, and (ii) a predefined threshold; identify a possible attachment point from (i) each sub-payload of the plurality of sub-payloads, and (ii) each exterior end of the payload, to obtain a plurality of possible attachment points, wherein each possible attachment point from each sub-payload is indicative of a center point in the associated sub-payload; obtain an attachment point position for each possible attachment point by considering one exterior end of the payload as a starting position and other exterior end of the payload as an ending position, wherein the starting position represents a zero position and the ending position represents a maximum position which is equivalent to the length of the payload; form one or more possible attachment point sets, from the plurality of possible attachment points, based on a safety distance criteria associated with the aerial vehicles, using associated attachment point positions, wherein each possible attachment point set comprises one or more possible attachment points out of the plurality of possible attachment points; determine a lift force for each possible attachment point present in each possible attachment point set of the one or more possible attachment point sets, based on the estimated weight distribution of the payload, using a slope deflection method; determine a bending moment for each possible attachment point of the plurality of possible attachment points, based on the associated lift force and the estimated weight distribution of the payload; determine (i) a differential lift force for each possible attachment point set of the one or more possible attachment point sets, based on the associated lift force for each of the one or more possible attachment points present in the associated possible attachment point set, and (ii) a mean separation distance for each possible attachment point set of the one or more possible attachment point sets, based on the attachment point position for each of the one or more possible attachment points present in the associated possible attachment point set; obtain a maximum absolute bending moment for each possible attachment point set of the one or more possible attachment point sets, by identifying the possible attachment point whose absolute bending moment is maximum and present across the one or more possible attachment points present in the corresponding possible attachment point set; determine one or more optimal attachment point sets out of the one or more possible attachment point sets, based on a predefined feasibility criteria, wherein the predefined feasibility criteria comprises one of: (A) determining if one possible attachment point set having a least differential lift force, is present, out of the one or more possible attachment point sets, and then classifying the possible attachment point set having the least differential lift force, as the optimal attachment point set; and (B) determining if multiple possible attachment point sets having the same least differential lift force, are present, out of the one or more possible attachment point sets, and then: (a) determining if one possible attachment point set having a least maximum absolute bending moment, is present, out of the multiple possible attachment point sets having the same least differential lift force, and then classifying the possible attachment point set having the least maximum absolute bending moment, as the optimal attachment point set; and (b) determining if multiple possible attachment point sets having the same least maximum bending moment, are present, out of the multiple possible attachment point sets having the same least differential lift force, and then: (i) determining if one possible attachment point set having a maximum mean separation distance, is present, out of the multiple possible attachment point sets having the same least maximum absolute bending moment, and then classifying the possible attachment point set having the maximum mean separation distance, as the optimal attachment point set; and (ii) determining if multiple possible attachment point sets having the same maximum mean separation distance, are present, out of the multiple possible attachment point sets having the same least maximum absolute bending moment, and then classifying the multiple possible attachment point sets having the same maximum mean separation distance, as multiple optimal attachment point sets; and classify the one or more possible attachment points present in each of the one or more optimal attachment point sets, as one or more optimal attachment points.
[007] In yet another aspect, there is provided a computer program product comprising a non-transitory computer readable medium having a computer readable program embodied therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: receive a number of the multiple aerial vehicles, and characteristics of a payload to be transported by the number of the multiple aerial vehicles, wherein the characteristics of the payload comprises: (i) a length of the payload, (ii) a total weight of the payload, and (iii) a center of gravity of the payload; estimate a weight distribution of the payload, based on (i) the characteristics of the payload to be transported, and (ii) a weight distribution feasibility criteria, wherein the weight distribution of the payload comprises weights that are uniformly distributed along the payload; virtually divide the payload into a plurality of sub-payloads, wherein a number of divisions of the payload is greater than or equal to a product of (i) the length of the payload, and (ii) a predefined threshold; identify a possible attachment point from (i) each sub-payload of the plurality of sub-payloads, and (ii) each exterior end of the payload, to obtain a plurality of possible attachment points, wherein each possible attachment point from each sub-payload is indicative of a center point in the associated sub-payload; obtain an attachment point position for each possible attachment point by considering one exterior end of the payload as a starting position and other exterior end of the payload as an ending position, wherein the starting position represents a zero position and the ending position represents a maximum position which is equivalent to the length of the payload; form one or more possible attachment point sets, from the plurality of possible attachment points, based on a safety distance criteria associated with the aerial vehicles, using associated attachment point positions, wherein each possible attachment point set comprises one or more possible attachment points out of the plurality of possible attachment points; determine a lift force for each possible attachment point present in each possible attachment point set of the one or more possible attachment point sets, based on the estimated weight distribution of the payload, using a slope deflection method; determine a bending moment for each possible attachment point of the plurality of possible attachment points, based on the associated lift force and the estimated weight distribution of the payload; determine (i) a differential lift force for each possible attachment point set of the one or more possible attachment point sets, based on the associated lift force for each of the one or more possible attachment points present in the associated possible attachment point set, and (ii) a mean separation distance for each possible attachment point set of the one or more possible attachment point sets, based on the attachment point position for each of the one or more possible attachment points present in the associated possible attachment point set; obtain a maximum absolute bending moment for each possible attachment point set of the one or more possible attachment point sets, by identifying the possible attachment point whose absolute bending moment is maximum and present across the one or more possible attachment points present in the corresponding possible attachment point set; determine one or more optimal attachment point sets out of the one or more possible attachment point sets, based on a predefined feasibility criteria, wherein the predefined feasibility criteria comprises one of: (A) determining if one possible attachment point set having a least differential lift force, is present, out of the one or more possible attachment point sets, and then classifying the possible attachment point set having the least differential lift force, as the optimal attachment point set; and (B) determining if multiple possible attachment point sets having the same least differential lift force, are present, out of the one or more possible attachment point sets, and then: (a) determining if one possible attachment point set having a least maximum absolute bending moment, is present, out of the multiple possible attachment point sets having the same least differential lift force, and then classifying the possible attachment point set having the least maximum absolute bending moment, as the optimal attachment point set; and (b) determining if multiple possible attachment point sets having the same least maximum bending moment, are present, out of the multiple possible attachment point sets having the same least differential lift force, and then: (i) determining if one possible attachment point set having a maximum mean separation distance, is present, out of the multiple possible attachment point sets having the same least maximum absolute bending moment, and then classifying the possible attachment point set having the maximum mean separation distance, as the optimal attachment point set; and (ii) determining if multiple possible attachment point sets having the same maximum mean separation distance, are present, out of the multiple possible attachment point sets having the same least maximum absolute bending moment, and then classifying the multiple possible attachment point sets having the same maximum mean separation distance, as multiple optimal attachment point sets; and classify the one or more possible attachment points present in each of the one or more optimal attachment point sets, as one or more optimal attachment points.
[008] In an embodiment, the weight distribution feasibility criteria comprises: determining whether (i) a total weight of the estimated weight distribution of the payload is equal to the total weight of the payload, and (ii) the center of gravity of the estimated weight distribution depends on linearly varying weights between exterior ends of the payload.
[009] In an embodiment, the number of the one or more possible attachment points present in each possible attachment point set is equivalent to the number of the aerial vehicles.
[010] In an embodiment, the lift force for each possible attachment point present in each possible attachment point set of the one or more possible attachment point sets, is determined, based on the estimated weight distribution of the payload, using a slope deflection method, by: determining a fixed end bending moment at the associated possible attachment point, based on the weight distribution of each sub-payload corresponding to the associated possible attachment point; determining a bending moment and a joint rotation angle at the associated possible attachment point, based on the associated fixed end bending moment, by using the slope deflection method; calculating a section wise force for each sub-payload corresponding to the associated possible attachment point, based on the bending moment and the joint rotation angle at the associated possible attachment point; and determining the lift force for the associated possible attachment point, based on the section wise force for each sub-payload corresponding to the associated possible attachment point.
[011] It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the embodiments of the present disclosure, as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS
[012] The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate exemplary embodiments and, together with the description, serve to explain the disclosed principles:
[013] FIG. 1 is an exemplary block diagram of a system for determining optimal attachment points on a payload for transportation by multiple aerial vehicles, in accordance with some embodiments of the present disclosure.
[014] FIG. 2A through FIG. 2C illustrate exemplary flow diagrams of a processor-implemented method for determining optimal attachment points on the payload for transportation by the multiple aerial vehicles, in accordance with some embodiments of the present disclosure.
[015] FIG. 3 shows an exemplary arrangement for estimating a weight distribution of the payload when a center of gravity of the payload and a geometric center of the payload does not coincide with each other, in accordance with some embodiments of the present disclosure.
[016] FIG. 4 shows division of the payload into a plurality of sub-payloads to obtain a plurality of possible attachment points, in accordance with some embodiments of the present disclosure.
[017] FIG. 5 shows attachment point position for each possible attachment point of the plurality of possible attachment points, in accordance with some embodiments of the present disclosure.

DETAILED DESCRIPTION OF EMBODIMENTS
[018] Exemplary embodiments are described with reference to the accompanying drawings. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. Wherever convenient, the same reference numbers are used throughout the drawings to refer to the same or like parts. While examples and features of disclosed principles are described herein, modifications, adaptations, and other implementations are possible without departing from the scope of the disclosed embodiments.
[019] The present disclosure herein provides methods and systems for determining optimal attachment points on payload for transportation using multiple aerial vehicles solve the technical problems for determining the optimal attachment points on the payload by ensuring that the weight of the payload is equally distributed among the multiple aerial vehicles and thus ensuring longer endurance for the payload being transported by the multiple aerial vehicles.
[020] In the context of the present disclosure, the term payload may be a heavy payload or a large payload, that may not be transported by a single aerial vehicle.
[021] Referring now to the drawings, and more particularly to FIG. 1 through FIG. 5, where similar reference characters denote corresponding features consistently throughout the figures, there are shown preferred embodiments and these embodiments are described in the context of the following exemplary systems and/or methods.
[022] FIG. 1 is an exemplary block diagram of a system 100 for determining optimal attachment points on a payload for transportation by the multiple aerial vehicles, in accordance with some embodiments of the present disclosure. In an embodiment, the system 100 includes or is otherwise in communication with one or more hardware processors 104, communication interface device(s) or input/output (I/O) interface(s) 106, and one or more data storage devices or memory 102 operatively coupled to the one or more hardware processors 104. The one or more hardware processors 104, the memory 102, and the I/O interface(s) 106 may be coupled to a system bus 108 or a similar mechanism.
[023] The I/O interface(s) 106 may include a variety of software and hardware interfaces, for example, a web interface, a graphical user interface, and the like. The I/O interface(s) 106 may include a variety of software and hardware interfaces, for example, interfaces for peripheral device(s), such as a keyboard, a mouse, an external memory, a plurality of sensor devices, a printer and the like. Further, the I/O interface(s) 106 may enable the system 100 to communicate with other devices, such as web servers and external databases.
[024] The I/O interface(s) 106 can facilitate multiple communications within a wide variety of networks and protocol types, including wired networks, for example, local area network (LAN), cable, etc., and wireless networks, such as Wireless LAN (WLAN), cellular, or satellite. For the purpose, the I/O interface(s) 106 may include one or more ports for connecting a number of computing systems with one another or to another server computer. Further, the I/O interface(s) 106 may include one or more ports for connecting a number of devices to one another or to another server.
[025] The one or more hardware processors 104 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions. Among other capabilities, the one or more hardware processors 104 are configured to fetch and execute computer-readable instructions stored in the memory 102. In the context of the present disclosure, the expressions ‘processors’ and ‘hardware processors’ may be used interchangeably. In an embodiment, the system 100 can be implemented in a variety of computing systems, such as laptop computers, portable computers, notebooks, hand-held devices, workstations, mainframe computers, servers, a network cloud and the like.
[026] The memory 102 may include any computer-readable medium known in the art including, for example, volatile memory, such as static random access memory (SRAM) and dynamic random access memory (DRAM), and/or non-volatile memory, such as read only memory (ROM), erasable programmable ROM, flash memories, hard disks, optical disks, and magnetic tapes. In an embodiment, the memory 102 includes a plurality of modules 102a and a repository 102b for storing data processed, received, and generated by one or more of the plurality of modules 102a. The plurality of modules 102a may include routines, programs, objects, components, data structures, and so on, which perform particular tasks or implement particular abstract data types.
[027] The plurality of modules 102a may include programs or computer-readable instructions or coded instructions that supplement applications or functions performed by the system 100. The plurality of modules 102a may also be used as, signal processor(s), state machine(s), logic circuitries, and/or any other device or component that manipulates signals based on operational instructions. Further, the plurality of modules 102a can be used by hardware, by computer-readable instructions executed by the one or more hardware processors 104, or by a combination thereof. In an embodiment, the plurality of modules 102a can include various sub-modules (not shown in FIG. 1). Further, the memory 102 may include information pertaining to input(s)/output(s) of each step performed by the processor(s) 104 of the system 100 and methods of the present disclosure.
[028] The repository 102b may include a database or a data engine. Further, the repository 102b amongst other things, may serve as a database or includes a plurality of databases for storing the data that is processed, received, or generated as a result of the execution of the plurality of modules 102a. Although the repository 102a is shown internal to the system 100, it will be noted that, in alternate embodiments, the repository 102b can also be implemented external to the system 100, where the repository 102b may be stored within an external database (not shown in FIG. 1) communicatively coupled to the system 100. The data contained within such external database may be periodically updated. For example, new data may be added into the external database and/or existing data may be modified and/or non-useful data may be deleted from the external database. In one example, the data may be stored in an external system, such as a Lightweight Directory Access Protocol (LDAP) directory and a Relational Database Management System (RDBMS). In another embodiment, the data stored in the repository 102b may be distributed between the system 100 and the external database.
[029] Referring to FIG. 2A through FIG. 2C, components and functionalities of the system 100 are described in accordance with an example embodiment of the present disclosure. For example, FIG. 2A through FIG. 2C illustrate exemplary flow diagrams of a processor-implemented method 200 for determining optimal attachment points on the payload for transportation by the multiple aerial vehicles, in accordance with some embodiments of the present disclosure. Although steps of the method 200 including process steps, method steps, techniques or the like may be described in a sequential order, such processes, methods and techniques may be configured to work in alternate orders. In other words, any sequence or order of steps that may be described does not necessarily indicate a requirement that the steps be performed in that order. The steps of processes described herein may be performed in any practical order. Further, some steps may be performed simultaneously, or some steps may be performed alone or independently.
[030] At step 202 of the method 200, the one or more hardware processors 104 of the system 100 are configured to receive a number (say n) of the multiple aerial vehicles, and characteristics of the payload to be transported by the number of the multiple aerial vehicles. In an embodiment, the multiple aerial vehicles may be unmanned aerial vehicles (UAVs) such as drones, multi rotor aerial vehicles, or a combination thereof.
[031] The characteristics of the payload comprises: (i) a length of the payload, (ii) a total weight of the payload, and (iii) a center of gravity of the payload. The payload contains a number of materials to be transported. For example, in time critical applications such as medicine and medical equipment support applications, the payload includes the medicines and medical devices that are to be transported from one location to another in emergency conditions of the patients. The payload may be a large payload which may not be transported by a single aerial vehicle. The shape of the payload may be a square, rectangle, circle, or any other polygon shape. However, in the context of the present disclosure, the shape of the payload is considered as rectangle. The length of the payload may be measured either in centimeters (cm) or meters (m). The total weight of the payload defines the weight of the payload may be measured in Newtons (N). The center of gravity (CG) of the payload defines an average location of the weight of the payload, where the weight is evenly dispersed, and all sides are in balance.
[032] In an embodiment, the number of the multiple aerial vehicles is determined based on the capacity limit of each aerial vehicle and one or more characteristics of the payload. For example, the number of the multiple aerial vehicles is determined based on the capacity limit of each aerial vehicle and the total weight of the payload. In another example, the number of the multiple aerial vehicles is determined based on the capacity of each aerial vehicle, the total weight of the payload, and the length of the payload, and so on. In the context of the present disclosure, dimensions such as size, and the capacity limit of each aerial vehicle among the multiple aerial vehicles, are same. Further, the controller of each aerial vehicle among the multiple aerial vehicles, is configured such that the swing angle of the cable attached to the aerial vehicle is minimal.
In the payload, the weight may not be uniformly distributed. At step 204 of the method 200, the one or more hardware processors 104 of the system 100 are configured to estimate a weight distribution of the payload received at step 202 of the method 200. The weight distribution of the payload is estimated based on (i) the characteristics of the payload to be transported, and (ii) a weight distribution feasibility criteria. The weight distribution of the payload includes the weights that are uniformly distributed along the payload. The weight distribution feasibility criteria includes determining whether the total weight of the estimated weight distribution of the payload is equal to the total weight of the payload, and the CG of the estimated weight distribution depends on linearly varying weights between exterior end points of the payload.
For example, let the length of the payload be L, a geometric center of the payload be C_tr, the CG of the payload be C_g, and the total weight of the payload be W_tot, then the weight at one exterior end (A) of the payload may be W_1 N/m, and weight at the other exterior end (B) of the payload may be W_2 N/m, where W_1 and W_2 are unknown and may be estimated based on a geometric center of the payload C_tr and the CG of the payload C_g. Here, the geometric center of the payload C_tr refers the midpoint of the payload which may be determined once the length of the payload be L is known. If the CG of the payload C_g and the geometric center of the payload C_tr coincides with each other then, W_1=W_2= W_tot/L.
If the CG of the payload C_g and the geometric center of the payload C_tr does not coincide with each other, then W_1 and W_2 may be estimated based on the weight distribution feasibility criteria..
More specifically, the first criteria tis the total weight of the estimated weight distribution of the payload is equal to the total weight of the payload W_tot, which may be written as in equation 1:
W_1 L+(W_2-W_1 )L/2=W_tot ---------------------------------------------(1)
FIG. 3 shows an exemplary arrangement for estimating the weight distribution of the payload when the CG of the payload C_gand the geometric center of the payload C_tr does not coincide with each other, in accordance with some embodiments of the present disclosure. Here A and B represents exterior end points of the payload. L_(C_g )represents the length of the payload from one exterior end (A) to the CG of the payload C_g, and L_(C_tr ) represents the length of the payload from one exterior end (A) to the geometric center of the payload C_tr. Based on FIG. 3, the second criteria the CG of the estimated weight distribution depends on linearly varying weights between end points of the payload, may be written as in equation 2:
L_(C_g )=(W_1 L (L/2)+(W_2-W_1 ) (L/2) (2L/3))/(W_1 L + (W_2-W_1 ) (L/2)) ---------------------------------------------(2)
By solving the equation 1 and equation 2, the weights W_1 and W_2 can be obtained. The weights W_1 and W_2 may represent maximum weight at one exterior end and minimum weight at another exterior end of the payload. Based on the weights W_1 and W_2, the weights that are uniformly distributed across the payload may be estimated.
At step 206 of the method 200, the one or more hardware processors 104 of the system 100 are configured to virtually divide the payload into a plurality of sub-payloads. The number of divisions of the payload is greater than or equal to a product of (i) the length of the payload, and (ii) a predefined threshold. The length of each sub-payload is same.
Higher the number of divisions, higher the number of sub-payloads and hence higher the accuracy. But the larger number of the divisions would incur larger computation cost such as processor and memory requirements. Thus, an optimal number of divisions is required to be found such that the accuracy is maintained and at the same time, the computational cost is not too high. So, a convergence study is carried out to find an appropriate length of the sub-payload for a particular length of the payload L. As the length of the sub-payload depends on the number of divisions D and the length of the payload L, the parameter D/L is studied against the residual sum square (RSS) of the desired attachment points for different lengths of payloads. The RSS value for the payloads of length ranging from 2m to 8m are found to converge within 2 * 10-3 beyond the D/L value of 50. Hence the predefined threshold is considered as 50, while calculating the number of divisions.
At step 208 of the method 200, the one or more hardware processors 104 of the system 100 are configured to identify a possible attachment point from each sub-payload of the plurality of payloads obtained at step 206 of the method 200 and the possible attachment point from each exterior end of the payload, to obtain a plurality of possible attachment points. Each possible attachment point for each sub-payload is indicative of a center point in the associated sub-payload. Note here that each of sub-payload present at exterior ends of the payload contains two possible attachment points, where one possible attachment point at extreme end and the second possible attachment point at the center point. FIG. 4 shows division of the payload into a plurality of sub-payloads to obtain a plurality of possible attachment points, in accordance with some embodiments of the present disclosure. From FIG. 4, the payload is divided into N number of the sub-payloads to obtain N+2 number of possible attachment points starting from the one exterior end with possible attachment point 1, the possible attachment point 2, and so on, the possible attachment point N+2 at another exterior end.
At step 210 of the method 200, the one or more hardware processors 104 of the system 100 are configured to obtain an attachment point position for each possible attachment point of the plurality of attachment points to obtain a plurality of attachment point positions for the plurality of possible attachment points. The attachment point position for each possible attachment point of the plurality of attachment points is obtained by considering one exterior end of the payload as a starting position and another exterior end of the payload as an ending position. The starting position represents a zero position and the ending position represents a maximum position which is equivalent to the length of the payload. For example, if the left exterior end of the payload is considered as the starting position of the payload, then the right exterior end of the payload is considered as the ending position of the payload, or vice versa. FIG. 5 shows attachment point position for each possible attachment point of the plurality of possible attachment points, in accordance with some embodiments of the present disclosure. From FIG. 5, the length of the payload is considered as 1 meter and is divided to 10 sub-payloads and hence 12 possible attachment points are obtained including from both exterior ends. The attachment point position at the starting possible attachment point at one exterior end is represented with ‘0.0’ meter (zero position) and the attachment point position at the last possible attachment point at the another exterior end is represented with ‘1.0’ meter (length of the payload). Subsequently, the attachment point positions for the remaining possible attachment points are obtained based on the center position of the associated sub-payload.
At step 212 of the method 200, the one or more hardware processors 104 of the system 100 are configured to form one or more possible attachment point sets, from the plurality of possible attachment points. The one or more possible attachment point sets are formed based on a safety distance criteria associated with the aerial vehicles and using associated attachment point positions. The safety distance criteria refer to the safety distance between the multiple aerial vehicles, so that a collision between the multiple aerial vehicles are avoided. The safety distance between multiple aerial vehicles is taken care, based on the associated attachment point positions.
Each possible attachment point set comprises one or more possible attachment points out of the plurality of possible attachment points. The number of the one or more possible attachment points present in each possible attachment point set is equivalent to the number of the multiple aerial vehicles, so that each aerial vehicle among the multiple aerial vehicles may the attached to each possible attachment point.
Table 1 shows five exemplary possible attachment point sets along with respective attachment point positions, considering the 3 aerial vehicles i, j, and k, required for transporting the payload having the length of the payload as 1 meter. From table 1, X_i, X_j and X_k represents three possible attachment points that may present in each possible attachment point set. Here the attachment point position 0.0 (in meter) indicates the starting position of the payload and the position 1.0 (in meter) indicates the ending position of the payload. The aerial i may be connected at the possible attachment point X_i, the aerial vehicle j may be connected at the possible attachment point X_j, and the aerial vehicle k may be connected at the possible attachment point X_k.
Possible attachment point set No X_i X_j X_k
1 0.0 0.5 1.0
2 0.1 0.5 0.9
3 0.2 0.5 0.8
4 0.3 0.5 0.7
5 0.4 0.5 0.6
Table 1
At step 214 of the method 200, the one or more hardware processors 104 of the system 100 are configured to determine a lift force for each possible attachment point present in each possible attachment point set of the one or more possible attachment point sets. The lift force for each possible attachment point represents the required force at the associated attachment point position for lifting the payload by the aerial vehicle connected to it. The lift force for each possible attachment point present in each possible attachment point set is determined based on the estimated weight distribution of the payload obtained at step 204 of the method, using a slope deflection method.
The reaction forces from the payload to the multiple aerial vehicles are determined using the force and moment balancing at each possible attachment point along the length of the payload. As the number of the multiple aerial vehicles is increased, the problem is complicated and the reaction forces are calculated by virtually dividing the payload into sections at the designated possible attachment point set and then applying the force and moment balancing on the divided sections individually. The sectional reaction forces for each possible attachment point present in the possible attachment point set thus calculated is superimposed to determine the net reaction forces at the possible attachment points.
Once the reaction forces at the possible attachment points are calculated, the fixed end bending moment is calculated as the product of the perpendicular force and the distance from the attachment point position where the fixed bending moment is calculated. In case of the distributed mass, the resultant perpendicular force is acting on the center of mass of the distributed mass from the initial attachment point till the attachment point where fixed bending moment is calculated. Thus, the fixed end bending moment is calculated at each point along the payload, starting from initial point of the payload till the end.
Determining the lift force for each possible attachment point present in each possible attachment point set, is further explained below. Firstly, a fixed end bending moment at the associated possible attachment point is determined, based on the weight distribution of each sub-payload corresponding to the associated possible attachment point.
Next, a bending moment and a joint rotation angle at the associated possible attachment point, are determined, based on the associated fixed end bending moment, by using the slope deflection method. The slope deflection method is a structural analysis method used for beams and frames. In the present disclosure, the slope deflection method is used by idealizing the payload as a simply supported beam with pinned joints. The slope deflection method includes slope deflection equations which defined the relation between the bending moment and the joint rotation angle.
Further, a section wise force for each sub-payload corresponding to the associated possible attachment point, is determined, based on the bending moment and the joint rotation angle at the associated possible attachment point. Lastly, the lift force for the associated possible attachment point, is determined, based on the section wise force for each sub-payload corresponding to the associated possible attachment point.
Table 2 shows the exemplary lift forces F[X_i ], F[X_j ], and
F[X_k ] for the three possible attachment points X_i, X_j and X_k respectively, present in each exemplary possible attachment point set shown in table 1. Note here that though the attachment point position for the possible attachment point X_j is same which is ‘0.5’ meter, however the lift force for possible attachment point X_j present in each possible attachment point set may vary with respect to other possible attachment points present in the respective possible attachment point sets.
Possible attachment point set No X_i X_j X_k F[X_i ] F[X_j ] F[X_k ]
1 0.0 0.5 1.0 1.33 1.33 1.33
2 0.1 0.5 0.9 1.5 1.4 1.6
3 0.2 0.5 0.8 1.33 1.33 1.33
4 0.3 0.5 0.7 0.8 1.6 1.6
5 0.4 0.5 0.6 1.33 1.33 1.33
Table 2
At step 216 of the method 200, the one or more hardware processors 104 of the system 100 are configured to determine a bending moment BM for each possible attachment point of the plurality of possible attachment points, identified for each sub-payload, at step 208 of the method 200. The bending moment BM for each possible attachment point of the plurality of possible attachment points is determined as mentioned at step 214 of the method 200, based on the associated lift force determined at step 212 of the method 200 and the estimated weight distribution of the payload obtained at step 204 of the method 200.
At step 218 of the method 200, the one or more hardware processors 104 of the system 100 are configured to determine (i) a differential lift force F_Dif for each possible attachment point set of the one or more possible attachment point sets, and (ii) a mean separation distance D_Mean for each possible attachment point set of the one or more possible attachment point sets. The differential lift force F_Dif (measured in Newtons (N)) for each possible attachment point set is determined based on the associated lift force for each of the one or more possible attachment points present in the associated possible attachment point set. For example, the differential lift force F_Dif for the three possible attachment points X_i, X_j and X_k is calculated by using equation 3:
The mean separation distance D_Mean for each possible attachment point set is determined based on the attachment point position for each of the one or more possible attachment points present in the associated possible attachment point set. For example, the mean separation distance D_Mean for the possible attachment point set having three possible attachment points X_i, X_j and X_k , is calculated by using equation 4:where N_AV is number of the multiple aerial vehicles received at step 202 of the method 200.
Table 3 shows the exemplary differential lift force F_Dif and the mean separation distance D_Mean for each exemplary possible attachment point set shown in table 1.
Possible attachment point set No X_i X_j X_k F[X_i ] F[X_j ] F[X_k ] F_Dif D_Mean
1 0.0 0.5 1.0 1.33 1.33 1.33 0 0.236
2 0.1 0.5 0.9 1.5 1.4 1.6 0.25 0.566
3 0.2 0.5 0.8 1.33 1.33 1.33 0 0.424
4 0.3 0.5 0.7 0.8 1.6 1.6 1.13 0.283
5 0.4 0.5 0.6 1.33 1.33 1.33 0 0.141
Table 3
At step 220 of the method 200, the one or more hardware processors 104 of the system 100 are configured to obtain a maximum absolute bending moment ?BM?_Max for each possible attachment point set of the one or more possible attachment point sets. The maximum absolute bending moment ?BM?_Max for each possible attachment point set is obtained by identifying the possible attachment point whose bending moment BM is maximum and the associated possible attachment point present across the one or more possible attachment points that are present in the corresponding possible attachment point set.
For example, from table 3, in the first possible attachment point set (row 1), the maximum absolute bending moment ?BM?_Max is obtained from the bending moments BM between the attachment point positions 0.0 and 1.0. More specifically, the bending moment BM that is maximum between the attachment point positions 0.0 and 1. 0 (i.e., 0.0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0) is considered as maximum absolute bending moment ?BM?_Max for the first possible attachment point set (row 1). Similarly, for the fifth possible attachment point set (row 5), the bending moment BM that is maximum between the attachment point positions 0.4 and 0.6 (i.e., 0.4, 0.5, 0.6) is considered as maximum absolute bending moment ?BM?_Max.
Table 4 shows the exemplary maximum absolute bending moments ?BM?_Max for each exemplary possible attachment point set shown in table 1, along with the differential lift force F_Dif and the mean separation distance D_Mean.
Possible attachment point set No X_i X_j X_k F[X_i ] F[X_j ] F[X_k ] F_Dif ?BM?_Max D_Mean
1 0.0 0.5 1.0 1.33 1.33 1.33 0 0.10 0.236
2 0.1 0.5 0.9 1.5 1.4 1.6 0.25 0.15 0.566
3 0.2 0.5 0.8 1.33 1.33 1.33 0 0.02 0.424
4 0.3 0.5 0.7 0.8 1.6 1.6 1.13 0.01 0.283
5 0.4 0.5 0.6 1.33 1.33 1.33 0 0.02 0.141
Table 4
At step 222 of the method 200, the one or more hardware processors 104 of the system 100 are configured to determine one or more optimal attachment point sets out of the one or more possible attachment point sets formed at step 212 of the method 200, based on a predefined feasibility criteria. The predefined feasibility criteria are defined based on the maximum absolute bending moments ?BM?_Max, differential lift force F_Dif, and the mean separation distance D_Mean for each possible attachment point set of the one or more possible attachment point sets. The predefined feasibility criteria to determine the one or more optimal attachment point sets out of the one or more possible attachment point sets is further explained in the below steps.
In the first step, one possible attachment point set having a least differential lift force F_Dif is determined from the one or more possible attachment point sets. If one possible attachment point set having the least differential lift force F_Dif, is present, out of the one or more possible attachment point sets, then the corresponding possible attachment point set having the least differential lift force F_Dif, is classified as the optimal attachment point set. Else, the second step is to be considered. The least differential lift force F_Dif represents the least power consumption by the aerial vehicle attached to the corresponding possible attachment point present in the possible attachment point set having the least differential lift force F_Dif.
In the second step, multiple possible attachment point sets having the same least differential lift force F_Dif are determined from the one or more possible attachment point sets. If multiple possible attachment point sets having the same least differential lift force F_Dif, are present, out of the one or more possible attachment point sets, then all the possible attachment point sets having the same least differential lift force F_Dif are considered for the third step. For example, from table 4, there are three possible attachment point sets 1, 3 and 5 (row 1, row 3, and row 5), having the same least differential lift force F_Dif with ‘0’. Hence, all the three possible attachment point sets 1, 3 and 5 are considered for the third step. Table 5 shows the three possible attachment point sets 1, 3 and 5 having the same least differential lift force F_Dif with ‘0’, to be considered for the third step.
Possible attachment point set No X_i X_j X_k F[X_i ] F[X_j ] F[X_k ] F_Dif ?BM?_Max D_Mean
1 0.0 0.5 1.0 1.33 1.33 1.33 0 0.10 0.236
3 0.2 0.5 0.8 1.33 1.33 1.33 0 0.02 0.424
5 0.4 0.5 0.6 1.33 1.33 1.33 0 0.02 0.141
Table 5
In the third step, one possible attachment point set having a least maximum absolute bending moment ?BM?_Max, is determined, out of the multiple possible attachment point sets having the same least differential lift force F_Dif, that are resultant from second step. If one possible attachment point set having the least maximum absolute bending moment ?BM?_Max, is present, then the corresponding possible attachment point set having the least maximum absolute bending moment ?BM?_Max, is classified as the optimal attachment point set. Else, the fourth step is to be considered. The least maximum absolute bending moment ?BM?_Max ensures either zero bending moment or minimum bending moment at the possible attachment point, when the aerial vehicle is attached to the corresponding possible attachment point present in the possible attachment point set having the least maximum absolute bending moment ?BM?_Max.
In the fourth step, multiple possible attachment point sets having the same least maximum bending moment ?BM?_Max are determined from the multiple possible attachment point sets having the same least differential lift force F_Dif, that are resultant from the third step. If multiple possible attachment point sets having the same least maximum bending moment ?BM?_Max, are present, then all the possible attachment point sets having the same least maximum bending moment ?BM?_Max are considered for the fifth step. For example, from table 5, there are two possible attachment point sets 3 and 5 (row 2 and row 5), having the same least maximum bending moment ?BM?_Max with ‘0.02’. Hence, all the two possible attachment point sets 3 and 5 are considered for the fifth step. Table 6 shows the two possible attachment point sets 3 and 5 having the same least maximum bending moment ?BM?_Max with ‘0.02’, to be considered for the fifth step.
Possible attachment point set No X_i X_j X_k F[X_i ] F[X_j ] F[X_k ] F_Dif ?BM?_Max D_Mean
3 0.2 0.5 0.8 1.33 1.33 1.33 0 0.02 0.424
5 0.4 0.5 0.6 1.33 1.33 1.33 0 0.02 0.141
Table 6
In the fifth step, one possible attachment point set having a maximum mean separation distance D_Mean, is determined, out of the multiple possible attachment point sets having the same least maximum absolute bending moment ?BM?_Max, that are resultant from fourth step. If one possible attachment point set having the maximum mean separation distance D_Mean, is present, then the corresponding possible attachment point set having the maximum mean separation distance D_Mean, is classified as the optimal attachment point set. Else, the sixth step is to be considered. The maximum mean separation distance D_Mean ensure towards zero collision between the multiple aerial vehicles, when the multiple aerial vehicles are attached to the corresponding possible attachment points present in the possible attachment point set having maximum mean separation distance D_Mean. For example, from table 6, there is only one possible attachment point set 3 (row 1), having the maximum mean separation distance D_Mean with ‘0.424’. Hence, the possible attachment point set 3 is classified as the optimal attachment point set out of the one or more possible attachment point sets shown in table 1.
In the sixth step, multiple possible attachment point sets having the same maximum mean separation distance D_Mean, are determined, out of the multiple possible attachment point sets having the same least maximum absolute bending moment ?BM?_Max, that are resultant from the fourth step. If multiple possible attachment point sets having the same having the same maximum mean separation distance D_Mean, are present, then all the multiple possible attachment point sets having the same maximum mean separation distance D_Mean are classified as the optimal attachment point sets.
Since there is only one possible attachment point set 3 (row 1) having the maximum mean separation distance D_Mean with ‘0.424’, is present, the predefined feasibility criteria ends with the fifth step, else the six step is to be considered. Note here that, if there are multiple possible attachment point sets having the same maximum mean separation distance D_Mean, are present, then two or more optimal attachment point sets are possible. The predefined feasibility criteria explained from first step to sixth step ensures to determine at least one optimal attachment point set out of the one or more possible attachment point sets formed at step 212 of the method 200, based on the maximum absolute bending moments ?BM?_Max, the differential lift force F_Dif, and the mean separation distance D_Mean for each possible attachment point set.
At step 224 of the method 200, one or more hardware processors 104 of the system 100 are configured to classify the one or more possible attachment points present in each of the one or more optimal attachment point sets determined at step 222 of the method 200, as one or more optimal attachment points. Each aerial vehicle of the multiple aerial vehicles is connected on each optimal attachment point of the one or more optimal attachment points on the payload.
For example, in the exemplary optimal attachment point set 3, the possible attachment points X_i, X_j and X_k at the attachment point positions ‘0.2’, ‘0.5’,and ‘0.8’, respectively are considered as optimal attachment points on the payload and the optimal attachment point positions are used to connect the multiple aerial vehicles for transporting the given payload.
In accordance with the present disclosure, the methods and systems determines the optimal attachment points on the payload, by ensuring that the weight of the payload is equally distributed among the multiple aerial vehicles and where the differential lift force F_Dif is minimum, the maximum absolute bending moment ?BM?_Max is minimum and the mean separation distance D_Mean of the multiple aerial vehicles is maximum. As the weight of the payload is equally distributed among multiple aerial vehicles while transporting, the power may be equally consumed by each aerial vehicle from their respective power sources and hence long endurance of the multiple aerial vehicles is achieved while transporting the payload. As the differential lift force F_Dif at each optimal attachment point is minimum, the aerial vehicle may consume less power. As the maximum absolute bending moment ?BM?_Max at each optimal attachment point is minimum, the control stability for each aerial vehicle is achieved. Further, the maximum mean separation distance D_Mean ensures zero collisions between the multiple aerial vehicles.
The methods and systems of the present disclosure may be used in numerous applications where the payload may not be transported by the single aerial vehicle. The applications include but are not limited to warehouse management applications, time critical applications such as medicine and medical equipment support applications, remote applications where road transport is difficult, and time consuming and so on. For example, in the medicine and medical equipment support applications, the multiple aerial vehicles may be used to transport the payload having medical equipment from one hospital to another hospital by avoiding the busy road traffic, in case of emergency.
Though the present disclosure is provided for determining the optimal attachment points on the payload for the multiple aerial vehicles of type UAVs such as drones, the scope of the present disclosure is not limited to UAVs. The present disclosure may also be used for manned aerial vehicles and a combination of the UAVs and the manned aerial vehicles.
The written description describes the subject matter herein to enable any person skilled in the art to make and use the embodiments. The scope of the subject matter embodiments is defined by the claims and may include other modifications that occur to those skilled in the art. Such other modifications are intended to be within the scope of the claims if they have similar elements that do not differ from the literal language of the claims or if they include equivalent elements with insubstantial differences from the literal language of the claims.
It is to be understood that the scope of the protection is extended to such a program and in addition to a computer-readable means having a message therein; such computer-readable storage means contain program-code means for implementation of one or more steps of the method, when the program runs on a server or mobile device or any suitable programmable device. The hardware device can be any kind of device which can be programmed including e.g. any kind of computer like a server or a personal computer, or the like, or any combination thereof. The device may also include means which could be e.g. hardware means like e.g. an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a combination of hardware and software means, e.g. an ASIC and an FPGA, or at least one microprocessor and at least one memory with software modules located therein. Thus, the means can include both hardware means and software means. The method embodiments described herein could be implemented in hardware and software. The device may also include software means. Alternatively, the embodiments may be implemented on different hardware devices, e.g. using a plurality of CPUs.
The embodiments herein can comprise hardware and software elements. The embodiments that are implemented in software include but are not limited to, firmware, resident software, microcode, etc. The functions performed by various modules described herein may be implemented in other modules or combinations of other modules. For the purposes of this description, a computer-usable or computer readable medium can be any apparatus that can comprise, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
The illustrated steps are set out to explain the exemplary embodiments shown, and it should be anticipated that ongoing technological development will change the manner in which particular functions are performed. These examples are presented herein for purposes of illustration, and not limitation. Further, the boundaries of the functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternative boundaries can be defined so long as the specified functions and relationships thereof are appropriately performed. Alternatives (including equivalents, extensions, variations, deviations, etc., of those described herein) will be apparent to persons skilled in the relevant art(s) based on the teachings contained herein. Such alternatives fall within the scope and spirit of the disclosed embodiments. Also, the words “comprising,” “having,” “containing,” and “including,” and other similar forms are intended to be equivalent in meaning and be open ended in that an item or items following any one of these words is not meant to be an exhaustive listing of such item or items, or meant to be limited to only the listed item or items. It must also be noted that as used herein and in the appended claims (when included in the specification), the singular forms “a,” “an,” and “the” include plural references unless the context clearly dictates otherwise.
Furthermore, one or more computer-readable storage media may be utilized in implementing embodiments consistent with the present disclosure. A computer-readable storage medium refers to any type of physical memory on which information or data readable by a processor may be stored. Thus, a computer-readable storage medium may store instructions for execution by one or more processors, including instructions for causing the processor(s) to perform steps or stages consistent with the embodiments described herein. The term “computer-readable medium” should be understood to include tangible items and exclude carrier waves and transient signals, i.e., be non-transitory. Examples include random access memory (RAM), read-only memory (ROM), volatile memory, nonvolatile memory, hard drives, CD ROMs, DVDs, flash drives, disks, and any other known physical storage media.
It is intended that the disclosure and examples be considered as exemplary only, with a true scope and spirit of disclosed embodiments being indicated by the following claims.