DESC:FIELD OF THE INVENTION
The present invention relates generally to an Unmanned Aerial Vehicle (UAV), and more particularly, to a method of battery failsafe estimation for Unmanned Aerial Vehicle (UAV) for managing battery energy at the time of mapping an area of interest (AOI).
BACKGROUND OF THE INVENTION
UAV based aerial mapping has become a prerequisite in many applications like urban planning, agriculture, mining etc. To map an area of interest (AOI) by an UAV, it generally takes multiple flights depending on the size of the AOI and the maximum flight time (endurance) of the UAV. Generally, aerial mapping of the AOI involves multiple flights depending on the size of AOI and the endurance of the UAV which introduces two major challenges in the execution of a typical aerial mapping project - critical battery situations, and handling the complexity of project planning with efficiency. The critical battery condition is undesirable while executing an aerial mapping project. It may lead to situations like emergency landing at unknown locations, and even more catastrophic consequences like crashes. Execution of an aerial mapping project of large AOI needs multiple flights. Every such flight needs to be planned independently during the execution which raises concerns of planning efficiency in the context of the whole project.
A patent no. US10372124B2 entitled “Electric unmanned aerial vehicle and an intelligent method of protecting electricity thereof” discloses an electric unmanned aerial vehicle that includes a position sensor configured to obtain coordinate information of the electric unmanned aerial vehicle in real-time, a memory storing coordinate information, and a controller in communication with the position sensor and the memory and being configured to calculate a safety electricity amount needed by the electric unmanned aerial vehicle to perform a safety protection command based on the coordinate information of the present position and the coordinate information of the preset position, compare the safety electricity amount with a present remaining electricity amount of a battery of the electric unmanned aerial vehicle, and perform a safety protection command if the present remaining electricity amount is not greater than the safety electricity amount.
A research paper entitled “Coverage Path Planning for UAVs Photogrammetry with Energy and Resolution Constraints” disclosing an Unmanned Aerial Vehicles (UAVs) are starting to be used for photogrammetric sensing of large areas in several application domains, such as agriculture, rescuing, and surveillance. It proposes an energy model derived from real measurements, and then uses this model to implement a coverage path planning algorithm for reducing energy consumption, as well as guaranteeing a desired image resolution. Also, two safety mechanisms are disclosed i.e. first one, executed off-line, checks whether the energy stored in the battery is sufficient to perform the planned path; the second one is, performed online, triggers a safe return-to-launch (RTL) operation when the actual available energy is equal to the energy required by the UAV to go back to the starting point.
Yet another patent no. US10068489B2 discloses a system and method for Managing energy during flight of unmanned aerial vehicles for safe return to ground. The disclosed system calculates a measure of remaining energy with regard to a UAV flying a mission plan and a measure of landing energy needed to travel to a landing station and can select a transition point from a mission plan and route leading from the mission plan to the landing station by comparing the calculated measure of remaining energy and the calculated measure of landing energy.
The primary issue with the known methods is that these methods used to avoid critical battery condition is by setting a Battery Failsafe Value below which the RTL is triggered automatically. The major problem in this kind of methods is if the distance to the land position from the RTL trigger location is large, the UAV might fail due to insufficient battery. This can be countered with increasing the failsafe value, but it results in Loss of Efficiency in terms of area coverage due to lesser flight time. So, the main problem is to identify a reliable battery failsafe value.
In order to overcome the aforementioned drawbacks, there is a need to provide an improved method of a battery failsafe estimation for an Unmanned Aerial Vehicle (UAV) to manage battery energy at the time of mapping an area of interest (AOI).
OBJECTIVES OF THE DISCLOSURE
A primary objective of the present invention is to overcome the disadvantages of the prior-arts.
Another objective of the present disclosure is to provide a method of battery failsafe estimation for an Unmanned Aerial Vehicle (UAV).
Yet another objective of the present disclosure is to manage battery energy at the time of mapping an area of interest (AOI) by the UAV.
Yet another objective of the present disclosure is to avoid a critical battery condition of the Unmanned Aerial Vehicle (UAV).
SUMMARY OF THE INVENTION
The following is a summary description of illustrative embodiments of the invention. It is provided as a preface to assist those skilled in the art to more rapidly assimilate the detailed design discussion which ensues and is not intended in any way to limit the scope of the claims which are appended hereto in order to particularly point out the invention.
An embodiment of the present invention relates to a method of battery failsafe estimation for an UAV (Unmanned Aerial Vehicle). The method includes analysing an initial battery voltage and a battery fail-safe voltage of the UAV by at least one controller. In addition, the method includes estimating a flight time of the UAV based on the initial battery voltage and the battery fail-safe voltage by at least one controller. The estimated flight time is estimated by using a plurality of times taken by the UAV for a plurality of phases. The method further includes identifying an RTL (Return to Launch) trigger location in a grid generated for an area of interest (AOI) mapping where an RTL (Return To Launch) command is to be triggered. The method also includes estimating a grid time based on the estimated flight time and the plurality of times of the plurality of phases by at least one controller. The method further includes estimating an iteration distance travelled by the UAV. The iteration distance is calculated by adding distances between each of a plurality of waypoint and a distance to a land position. The method concludes by determining an iteration time and compares it with the flight time to perform an operation by the UAV by at least one controller.
In accordance with an embodiment of the present invention, the identified RTL trigger location serves as a starting waypoint for a next phase of the AOI mapping.
In accordance with an embodiment of the present invention, the at least one controller is a flight controller.
In accordance with an embodiment of the present invention, the flight plan includes a launch waypoint and a landing waypoint that is set within a geo fence boundary.
In accordance with an embodiment of the present invention, the flight plan further includes a sequence of commands that is anyone of the RTL command, a take-Off command, a home command, a battery failsafe event command, a waypoint position command, a camera command, a hover command, a land command, among others.
In accordance with an embodiment of the present invention, the plurality of times includes a take-off time, a landing phase time, and a lag time added at every turn covered by the UAV.
In accordance with an embodiment of the present invention, the plurality of phases includes a landing phase, a take-off phase, a lag phase, a grid phase, a return to landing position (RTL)phase.
In accordance with an embodiment of the present invention, the operations are based on any one of a condition when the iteration time is greater than or equal to the flight time then the UAV covers the iteration Distance and lands back at the RTL trigger location and the iteration time is less than the flight time then the UAV does not transverse the iteration distance and the waypoint used in a previous iteration is taken as a last waypoint for a current flight.
In accordance with an embodiment of the present invention, the grid is generated as a plurality of parallel lines covering the AOI at a minimum possible distance.
In accordance with an embodiment of the present invention, the grid time is time spent by the UAV in the grid phase.
In accordance with an embodiment of the present invention, the lag time is the time spent at each turn in which the UAV decelerates and accelerates to its designated speed.
In accordance with an embodiment of the present invention, the take-off time is the time spent by the UAV in the take-off phase.
In accordance with an embodiment of the present invention, the landing phase time is the time spent by the UAV in the landing phase.
In accordance with an embodiment of the present invention, the at least one controller includes a memory for storing an information related to the flight plan.
In accordance with an embodiment of the present invention, a plurality of sensors is configured for determining a position of the UAV in the plurality of phases.
In accordance with an embodiment of the present invention, the plurality of sensors is anyone of a position sensor, a GPS sensor, a height sensor, alike.
In accordance with an embodiment of the present invention, the height sensor comprises at least one of a barometric altimeter, a laser altimeter, a radio altimeter, an ultrasound wave altimeter, or an image distance-measuring sensor.
These and other aspects herein will be better appreciated and understood when considered in conjunction with the following description and the accompanying drawing.
It should be understood, however, that the following descriptions are given by way of illustration and not of limitation. Many changes and modifications may be made within the scope of the invention herein without departing from the spirit thereof. The foregoing objectives are attained by employing an automatic salt level sensing device and a method of indicating a low salt level thereof.
BRIEF DESCRIPTION OF THE DRAWINGS
To describe the technical solutions in the embodiments of the present disclosure or in the prior art more clearly, the following briefly describes the accompanying drawings required for describing the embodiments or the prior art. Apparently, the accompanying drawings in the following description merely show some embodiments of the present disclosure, and a person of ordinary skill in the art can derive other implementations from these accompanying drawings without creative efforts. All of the embodiments or the implementations shall fall within the protection scope of the present disclosure. Having thus described the disclosure in general terms, reference will now be made to the accompanying figures.
Fig. 1 is a block diagram illustrating a method of battery failsafe estimation for an UAV (Unmanned Aerial Vehicle), in accordance with an embodiment of the present invention.
It should be noted that the accompanying figure is intended to present illustrations of a few examples of the present disclosure. The figure is not intended to limit the scope of the present disclosure. It should also be noted that the accompanying figure is not necessarily drawn to scale.
DETAILED DESCRIPTION OF THE INVENTION
In the following detailed description of the invention, numerous specific details are set forth in order to provide a thorough understanding of the invention. However, it will be obvious to a person skilled in the art that the invention may be practiced with or without these specific details. In other instances, well known methods, procedures and components have not been described in detail so as not to unnecessarily obscure aspects of the invention.
The accompanying drawing is used to help easily understand various technical features and it should be understood that the alternatives presented herein are not limited by the accompanying drawing. As such, the present disclosure should be construed to extend to any alterations, equivalents and substitutes in addition to those which are particularly set out in the accompanying drawing. Although the terms first, second, etc. may be used herein to describe various elements or values, these elements or values should not be limited by these terms. These terms are generally only used to distinguish one element or values from another.
It will be apparent to those skilled in the art that other alternatives of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention. While the foregoing written description of the invention enables one of ordinary skill to make and use what is considered presently to be the best mode thereof, those of ordinary skill will understand and appreciate the existence of variations, combinations, and equivalents of the specific aspect, method, and examples herein. The invention should therefore not be limited by the above-described alternative, method, and examples, but by all aspects and methods within the scope of the invention. It is intended that the specification and examples be considered as exemplary, with the true scope of the invention being indicated by the claims.
Conditional language used herein, such as, among others, "can," "may," "might," "may," “e.g.,” and the like, unless specifically stated otherwise, or otherwise understood within the context as used, is generally intended to convey that certain alternatives include, while other alternatives do not include, certain features, elements and/or steps. Thus, such conditional language is not generally intended to imply that features, elements and/or steps are in any way required for one or more alternatives or that one or more alternatives necessarily include logic for deciding, with or without other input or prompting, whether these features, elements and/or steps are included or are to be performed in any particular alternative. The terms “comprising,” “including,” “having,” and the like are synonymous and are used inclusively, in an open-ended fashion, and do not exclude additional elements, features, acts, operations, and so forth. Also, the term “or” is used in its inclusive sense (and not in its exclusive sense) so that when used, for example, to connect a list of elements, the term “or” means one, some, or all of the elements in the list.
Terms unmanned aerial vehicle or UAV may be used interchangeably for convenience.
Terms area of interest or AOI may be used interchangeably for convenience.
Terms return to land or RTL may be used interchangeably for convenience.
Fig. 1 is a block diagram 100 of a method of battery failsafe estimation for an unmanned aerial vehicle in accordance with one embodiment of the present disclosure. In general, the Unmanned Aerial Vehicle (UAV) is an aircraft that is operated or piloted by remote control and the RTL is a command that returns the UAV to the home position. In addition, the battery fail-safe is an event triggered by the UAV in case of a critical battery condition in which the UAV is expected to perform RTL. In accordance with an embodiment of the present invention, the block diagram starts at a step 105 and terminates at a step 130.

In particular, the method measures a flight time of the unmanned aerial vehicle and the distance at which the unmanned aerial vehicle performs a return to land (RTL). The UAV performs aerial mapping of an aera of interest (AOI) by following the path of a grid. The grid includes a plurality of waypoints which are followed by the UAV to perform the aerial mapping of the AOI.

At step 105, an initial battery voltage and a battery fail-safe voltage of the UAV is analyzed by at least one controller. In accordance with an embodiment of the present invention, the at least one controller includes one or more processors and a memory. The one or more processors is in communication with the memory to perform a series of computer-executable instructions stored in the memory related to a flight plan to be followed by the UAV.

The one or more processors associated with the at least one controller may be any well-known processor, but not limited to processors from Intel Corporation. Alternatively, the processor may be a dedicated controller such as an ASIC or ARM, MIPS, SPARC, or INTEL® IA-32 microcontroller or the like. In an implementation, the at least one controller is a flight controller.
In yet another embodiment of the present invention, the one or more processors comprise a collection of processors which may or may not operate in parallel. Alternatively, the one or more processors, which may be any processor-driven device, such as one or more microprocessors and memories or other computer-readable media operable for storing and executing computer-readable instructions.
The memory associated with the one or more processor stores instructions to be executed by the at least one controller. The memory can be any type of suitable memory, including various types of dynamic random access memory (DRAM) such as SDRAM, various types of static RAM (SRAM), and various types of non-volatile memory (PROM, EPROM, and flash). It should be understood that the memory may be a single type of memory component or it may be composed of many different types of memory components. As noted above, the memory stores instructions for executing one or more methods for estimating battery failsafe of the UAV (Unmanned Aerial Vehicle). For example, the memory may store software used by the user device, such as an operating system (not shown), application programs (not shown), and an associated internal database (not shown).
In accordance with an embodiment of the present disclosure, the flight plan is a sequence of commands followed by the UAV to complete a mapping of the area of interest. The sequence of commands includes RTL command, a take-Off command, a home command, a battery failsafe event command, a waypoint position command, a camera command, a hover command, a land command, among others. In accordance with an embodiment of the present invention, the flight plan includes a launch waypoint and a landing waypoint that is set within a geo fence boundary.

In an exemplary embodiment, Fig. 2 is providing the flight plan 200 of the UAV. The flight plan comprising the sequence of commands followed by the UAV to complete the mapping of area of interest 202. Further, The UAV performs aerial mapping of the aera of interest (AOI) 202 by following the path of a grid 204, which has the starting point i.e. a home location 208 and one or more RTL trigger locations 210 and one or more waypoints 206.

At step 110, the flight time of the UAV is estimated based on the initial battery voltage and the battery fail-safe voltage. In an embodiment of the present invention, the flight is estimated based on two conditions. The first condition includes the initial battery voltage and the battery fail-safe voltage of the UAV. The second condition includes estimating the flight time by using a plurality of times taken by the UAV for a plurality of phases. In an embodiment of the present invention, the plurality of phases includes a landing phase, a take-off phase, a lag phase, a grid phase, a return to landing position (RTL) phase. In addition, the plurality of times includes a take-off time, a landing phase time, and a lag time added at every turn covered by the UAV.
In an accordance to an embodiment of the present invention, the lag time is the time spent at each turn in which the UAV decelerates and accelerates to its designated speed. The take-off time is the time spent by the UAV in the take-off phase. In addition, the landing phase time is the time spent by the UAV in the landing phase. Further, the take-off time and the landing time are calculated based upon the climb and descent rate of the UAV which is controlled by the at least one controller.

In accordance with an embodiment of the present invention, a plurality of sensors is configured for determining the position of the UAV in the plurality of phases. The plurality of sensors is anyone of a position sensor, a GPS sensor, a height sensor, alike. The height sensor comprises at least one of a barometric altimeter, a laser altimeter, a radio altimeter, an ultrasound wave altimeter, or an image distance-measuring sensor.

At step 115, a RTL (Return to Launch) trigger location is identified in the grid generated for the area of interest (AOI) mapping by the at least one controller. In addition, a RTL (Return to Launch) command is triggered at the identified return to launch location. In accordance with an embodiment of the present invention, the identified RTL trigger location serves as a starting waypoint for a next phase of the AOI mapping.

At step 120, a grid time is estimated based on the estimated flight time and the plurality of times of the plurality of phases. The grid time is time spent by the UAV in the grid phase.

In accordance with an embodiment of the present invention, the grid time is calculated by subtracting the added result of the landing phase time, the take-off phase time and the lag factor added for turns from the total flight time. In addition, the distance covered by the UAV in the flight is calculated by adding a new position waypoint in every iteration of the flight.
In an example:
?T_Grid = T?_(flight ) - (T_(Take-off) + T_Landing + nturns*T_Lag)
where T_Grid: grid phase time; T_flight: total flight time; T_(Take-off): take-off phase time; T_landing: Landing phase time; T_Lag:Lag factor.

At step 125, an iteration distance travelled by the UAV is estimated by the at least one controller. In accordance with an embodiment of the present invention, the iteration distance is calculated by adding distances between each of the plurality of waypoints and a distance to a land position.

At step 130, an iteration time is determined by the at least one controller and compared with the flight time to perform an operation by the UAV. The iteration time is calculated by multiplying the iteration distance with the speed of the UAV.

In accordance with an embodiment of the present invention, the operation of the UAV is based on the two conditions. The first condition implies that the UAV covers the iteration distance and lands back at the RTL trigger location when the iteration time is greater than or equal to the flight time of the UAV. Further, the second condition implies that the UAV fails to transverse the iteration distance when the iteration time is less than the flight time. The waypoint used in a previous iteration is taken as a last waypoint for a current flight when the UAV fails to transverse the iteration distance. In addition, a new waypoint is identified by adding the distance UAV can transverse in the remaining flight time which is the difference between the flight time and the iteration time. The new waypoint is identified as the RTL trigger location to ensure efficiency in area coverage. Further, a new flight plan is generated with this RTL trigger location and sent to the UAV.

In an embodiment of the present invention, during the full operation the speed of the UAV is assumed constant. The current drawn by the flight has an averaged out approximate value. In addition, the difference of power required for acceleration and deceleration at turns and climbing and descending at the home location is averaged out and assumed constant.
While the detailed description has shown, described, and pointed out novel features as applied to various alternatives, it can be understood that various omissions, substitutions, and changes in the form and details of the devices or algorithms illustrated can be made without departing from the scope of the disclosure. As can be recognized, certain alternatives described herein can be embodied within a form that does not provide all of the features and benefits set forth herein, as some features can be used or practiced separately from others.
The disclosures and the description herein are intended to be illustrative and are not in any sense limiting the invention, defined in scope by the following claims.
,CLAIMS:We Claim:
1. A method of battery failsafe estimation for a UAV (Unmanned Aerial Vehicle), comprising:
analyzing, by at least one controller, an initial battery voltage and a battery fail-safe voltage of the UAV;
estimating, by at least one controller, a flight time of the UAV based on the initial battery voltage and the battery fail-safe voltage, wherein the estimated flight time is estimated by using a plurality of times taken by the UAV for a plurality of phases;
identifying, by the at least one controller, an RTL (Return to Land) trigger location in a grid generated for an area of interest mapping where an RTL (Return to Land) command is to be triggered;
estimating, by the at least one controller, a grid time based on the estimated flight time and the plurality of times of the plurality of phases;
estimating, by the at least one controller, an iteration distance travelled by the UAV, wherein the iteration distance is calculated by adding distances between each of a plurality of waypoint and a distance to a land position; and
determining, by the at least one controller, an iteration time and compare it with the flight time to perform an operation by the UAV.
2. The method as claimed in claim 1, wherein the identified RTL trigger location serves as a starting waypoint for a next phase of the area of interest mapping.
3. The method as claimed in claim 1, wherein the at least one controller is a flight controller.
4. The method as claimed in claim 1, wherein the flight plan includes a launch waypoint and a landing waypoint that is set within a geo fence boundary.
5. The method as claimed in claim 1, wherein the flight plan includes a sequence of commands that is anyone of the RTL command, a take-Off command, a home command, a battery failsafe event command, a waypoint position command, a camera command, a hover command, a land command, among others.
6. The method as claimed in claim 1, wherein the plurality of times includes a take-off time, a landing phase time, and a lag time added at every turn covered by the UAV.
7. The method as claimed in claim 1, wherein the plurality of phases includes a landing phase, a take-off phase, a lag phase, a grid phase, a return to landing position (RTL) phase.
8. The method as claimed in claim 1, wherein the operations is based on any one of a condition, when:
the iteration time is greater than or equal to the flight time then the UAV covers the iteration Distance and lands back at the RTL trigger location; and
the iteration time is less than the flight time then the UAV does not transverse the iteration distance and the waypoint used in a previous iteration is taken as a last waypoint for a current flight.
9. The method as claimed in claim 1, wherein the grid is generated as a plurality of parallel lines covering the area of interest at a minimum possible distance.
10. The method as claimed in claim 1, wherein the grid time is time spent by the UAV in the grid phase.
11. The method as claimed in claim 6, wherein the lag time is the time spent at each turn in which the UAV decelerates and accelerates to its designated speed.
12. The method as claimed in claim 6, wherein the take-off time is the time spent by the UAV in the take-off phase.
13. The method as claimed in claim 6, wherein the landing phase time is the time spent by the UAV in the landing phase.
14. The method as claimed in claim 1, wherein the at least one controller includes a memory for storing an information related to the flight plan.
15. The method as claimed in claim 1, wherein a plurality of sensors is configured for determining a position of the UAV in the plurality of phases.
16. The method as claimed in claim 15, wherein the plurality of sensors is anyone of a position sensor, a GPS sensor, a height sensor, alike.
17. The method as claimed in claim 16, wherein the height sensor comprises at least one of a barometric altimeter, a laser altimeter, a radio altimeter, an ultrasound wave altimeter, or an image distance-measuring sensor.