Method And System For Correcting A Pre‐Generated Navigation Path For An Autonomous Vehicle

Wipro Limited
Granted App No 201741034784 Patent 405477 Communication

Patent information

IP India · live record
Application number
201741034784
Filing date
29 September 2017
Status
Granted
Legal status
Inforce
Publication number
14/2019
Publication type
INA
Invention field
Communication
Patent number
405477
Grant date
01 September 2022
Next renewal due
29 September 2027

Abstract

This disclosure relates generally to autonomous vehicle, and more particularly to method and system for correcting a pre-generated navigation path for an autonomous vehicle. In one embodiment, a method may be provided for correcting the pre-generated navigation path for the autonomous vehicle. The method may include receiving the pre-generated navigation path on a navigation map, an environmental field of view (FOV) of the autonomous vehicle, and a location of the autonomous vehicle on the pre-generated navigation path. The method may further include determining a set of new data points in a pre-defined region with respect to the location of autonomous vehicle based on the environmental FOV and the navigation map, determining an offset of the pre-generated navigation path in the pre-defined region based on the set of new data points, and correcting the pre-generated navigation path in the pre-defined region based on the offset. Figure 2

Applicants

1
India
WIPRO LIMITED Doddakannelli, Sarjapur Road, Bangalore 560035, Karnataka, India

Inventors

3
India
BALAJI SUNIL KUMAR#001, BM Mystic Green, 27th Main Road, Sector 2, HSR Layout, Bengaluru 560102, Karnataka, India
India
MANAS SARKAR648, Rishi Bankim Sarani, Hridaypur, Barasat, North 24 Parganas, Kolkata‐ 700127, West Bengal, India
India
SHYAM SUNDAR PALFlat No: 14, Block: L/J, Kustia Govt. Housing Estate, Picnic Garden Road, Kolkata‐700039, West Bengal, India

Claims

16
1 A method for correcting a pre-generated navigation path for an autonomous vehicle, the method comprising: receiving, by a navigation device, the pre-generated navigation path on a navigation map, an environmental field of view (FOV) of the autonomous vehicle, and a location of the autonomous vehicle on the pre-generated navigation path; determining, by the navigation device, a set of new data points in a pre-defined region with respect to the location of autonomous vehicle based on the environmental FOV and the navigation map; determining, by the navigation device, an offset of the pre-generated navigation path in the pre-defined region based on the set of new data points; and correcting, by the navigation device, the pre-generated navigation path in the pre-defined region based on the offset.
2 The method of claim 1, wherein the navigation map is a pre-generated light detection and ranging (LIDAR) map, and wherein the environmental FOV is received from a LIDAR scanner.
3 The method of claim 1, wherein the location of the autonomous vehicle is determined using at least one of a Monte Carlo localization algorithm, a geo-positioning system, a visual odometer, and an odometer.
4 The method of claim 1, wherein the pre-defined region is a region up to a certain pre-defined distance in front of the autonomous vehicle based on a curvature of the pre-generated navigation path, along each side of the pre-generated navigation path, from a pre-defined start height above a road surface, and up to a pre-defined end height above the road surface.
5 The method of claim 1, wherein determining the set of new data points comprises: comparing a plurality of data points in the pre-defined region of the environmental FOV with a plurality of data points in the pre-defined region of the navigation map; and based on the comparison, identifying a set of data points in the pre-defined region of the environmental FOV that have no corresponding data points in the navigation map within a pre-defined threshold.
6 The method of claim 1, wherein determining the offset comprises determining a set of offset distances along the pre-generated navigation path with respect to the set of new data points.
7 The method of claim 6, wherein determining each of the set of offset distances comprises: projecting a virtual ray at a pre-defined projection angle from the autonomous vehicle; computing a distances between the autonomous vehicle and a first data point from the set of new data points in the line of the virtual ray; and computing an offset distance between the pre-generated navigation path and the first data point based on the distance and the pre-defined projection angle.
8 The method of claim 6, wherein correcting the pre-generated navigation path comprises: determining an actual drivable road width along the pre-generated navigation path in the pre-defined region based on the set of offset distances; and determining a corrected navigation path, corresponding to the pre-generated navigation path in the pre-defined region, based on the actual drivable road width.
9 The method of claim 6, wherein correcting the pre-generated navigation path comprises: identifying an intended distance of the autonomous vehicle from an obstacle or a no-go region of at least one side along the pre-generated navigation path in the pre-defined region; and determining a corrected navigation path, corresponding to the pre-generated navigation path in the pre-defined region, based on the intended distance and the set of offset distances.
10 A system for correcting a pre-generated navigation path for an autonomous vehicle, the system comprising: a navigation device comprising at least one processor and a computer-readable medium storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations comprising: receiving the pre-generated navigation path on a navigation map, an environmental field of view (FOV) of the autonomous vehicle, and a location of the autonomous vehicle on the pre-generated navigation path; determining a set of new data points in a pre-defined region with respect to the location of autonomous vehicle based on the environmental FOV and the navigation map; determining an offset of the pre-generated navigation path in the pre-defined region based on the set of new data points; and correcting the pre-generated navigation path in the pre-defined region based on the offset.
11 The system of claim 10, wherein the pre-defined region is a region up to a certain pre-defined distance in front of the autonomous vehicle based on a curvature of the pre-generated navigation path, along each side of the pre-generated navigation path, from a pre-defined start height above a road surface and up to a pre-defined end height above the road surface.
12 The system of claim 10, wherein determining the set of new data points comprises: comparing a plurality of data points in the pre-defined region of the environmental FOV with a plurality of data points in the pre-defined region of the navigation map; and based on the comparison, identifying a set of data points in the pre-defined region of the environmental FOV that have no corresponding data points in the navigation map within a pre-defined threshold.
13 The system of claim 10, wherein determining the offset comprises determining a set of offset distances along the pre-generated navigation path with respect to the set of new data points.
14 The system of claim 13, wherein determining each of the set of offset distances comprises: projecting a virtual ray at a pre-defined projection angle from the autonomous vehicle; computing a distances between the autonomous vehicle and a first data point from the set of new data points in the line of the virtual ray; and computing an offset distance between the pre-generated navigation path and the first data point based on the distance and the pre-defined projection angle.
15 The system of claim 13, wherein correcting the pre-generated navigation path comprises: determining an actual drivable road width along the pre-generated navigation path in the pre-defined region based on the set of offset distances; and determining a corrected navigation path, corresponding to the pre-generated navigation path in the pre-defined region, based on the actual drivable road width.
16 The system of claim 13, wherein correcting the pre-generated navigation path comprises: identifying an intended distance of the autonomous vehicle from an obstacle or a no-go region of at least one side along the pre-generated navigation path in the pre-defined region; and determining a corrected navigation path, corresponding to the pre-generated navigation path in the pre-defined region, based on the intended distance and the set of offset distances. Dated this 29th day of September, 2017 Swetha SN Of K&S Partners Agent for the Applicant IN/PA-2123 , Description:TECHNICAL FIELD This disclosure relates generally to autonomous vehicle, and more particularly to method and system for correcting a pre-generated navigation path for an autonomous vehicle.

Specification

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Claims:WE CLAIM 1. A method for correcting a pre-generated navigation path for an autonomous vehicle, the method comprising: receiving, by a navigation device, the pre-generated navigation path on a navigation map, an environmental field of view (FOV) of the autonomous vehicle, and a location of the autonomous vehicle on the pre-generated navigation path; determining, by the navigation device, a set of new data points in a pre-defined region with respect to the location of autonomous vehicle based on the environmental FOV and the navigation map; determining, by the navigation device, an offset of the pre-generated navigation path in the pre-defined region based on the set of new data points; and correcting, by the navigation device, the pre-generated navigation path in the pre-defined region based on the offset.

2. The method of claim 1, wherein the navigation map is a pre-generated light detection and ranging (LIDAR) map, and wherein the environmental FOV is received from a LIDAR scanner.

3. The method of claim 1, wherein the location of the autonomous vehicle is determined using at least one of a Monte Carlo localization algorithm, a geo-positioning system, a visual odometer, and an odometer.

4. The method of claim 1, wherein the pre-defined region is a region up to a certain pre-defined distance in front of the autonomous vehicle based on a curvature of the pre-generated navigation path, along each side of the pre-generated navigation path, from a pre-defined start height above a road surface, and up to a pre-defined end height above the road surface.

5. The method of claim 1, wherein determining the set of new data points comprises: comparing a plurality of data points in the pre-defined region of the environmental FOV with a plurality of data points in the pre-defined region of the navigation map; and based on the comparison, identifying a set of data points in the pre-defined region of the environmental FOV that have no corresponding data points in the navigation map within a pre-defined threshold.

6. The method of claim 1, wherein determining the offset comprises determining a set of offset distances along the pre-generated navigation path with respect to the set of new data points.

7. The method of claim 6, wherein determining each of the set of offset distances comprises: projecting a virtual ray at a pre-defined projection angle from the autonomous vehicle; computing a distances between the autonomous vehicle and a first data point from the set of new data points in the line of the virtual ray; and computing an offset distance between the pre-generated navigation path and the first data point based on the distance and the pre-defined projection angle.

8. The method of claim 6, wherein correcting the pre-generated navigation path comprises: determining an actual drivable road width along the pre-generated navigation path in the pre-defined region based on the set of offset distances; and determining a corrected navigation path, corresponding to the pre-generated navigation path in the pre-defined region, based on the actual drivable road width.

9. The method of claim 6, wherein correcting the pre-generated navigation path comprises: identifying an intended distance of the autonomous vehicle from an obstacle or a no-go region of at least one side along the pre-generated navigation path in the pre-defined region; and determining a corrected navigation path, corresponding to the pre-generated navigation path in the pre-defined region, based on the intended distance and the set of offset distances.

10. A system for correcting a pre-generated navigation path for an autonomous vehicle, the system comprising: a navigation device comprising at least one processor and a computer-readable medium storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations comprising: receiving the pre-generated navigation path on a navigation map, an environmental field of view (FOV) of the autonomous vehicle, and a location of the autonomous vehicle on the pre-generated navigation path; determining a set of new data points in a pre-defined region with respect to the location of autonomous vehicle based on the environmental FOV and the navigation map; determining an offset of the pre-generated navigation path in the pre-defined region based on the set of new data points; and correcting the pre-generated navigation path in the pre-defined region based on the offset.

11. The system of claim 10, wherein the pre-defined region is a region up to a certain pre-defined distance in front of the autonomous vehicle based on a curvature of the pre-generated navigation path, along each side of the pre-generated navigation path, from a pre-defined start height above a road surface and up to a pre-defined end height above the road surface.

12. The system of claim 10, wherein determining the set of new data points comprises: comparing a plurality of data points in the pre-defined region of the environmental FOV with a plurality of data points in the pre-defined region of the navigation map; and based on the comparison, identifying a set of data points in the pre-defined region of the environmental FOV that have no corresponding data points in the navigation map within a pre-defined threshold.

13. The system of claim 10, wherein determining the offset comprises determining a set of offset distances along the pre-generated navigation path with respect to the set of new data points.

14. The system of claim 13, wherein determining each of the set of offset distances comprises: projecting a virtual ray at a pre-defined projection angle from the autonomous vehicle; computing a distances between the autonomous vehicle and a first data point from the set of new data points in the line of the virtual ray; and computing an offset distance between the pre-generated navigation path and the first data point based on the distance and the pre-defined projection angle.

15. The system of claim 13, wherein correcting the pre-generated navigation path comprises: determining an actual drivable road width along the pre-generated navigation path in the pre-defined region based on the set of offset distances; and determining a corrected navigation path, corresponding to the pre-generated navigation path in the pre-defined region, based on the actual drivable road width.

16. The system of claim 13, wherein correcting the pre-generated navigation path comprises: identifying an intended distance of the autonomous vehicle from an obstacle or a no-go region of at least one side along the pre-generated navigation path in the pre-defined region; and determining a corrected navigation path, corresponding to the pre-generated navigation path in the pre-defined region, based on the intended distance and the set of offset distances.

Dated this 29th day of September, 2017

Swetha SN Of K&S Partners Agent for the Applicant IN/PA-2123 , Description:TECHNICAL FIELD

This disclosure relates generally to autonomous vehicle, and more particularly to method and system for correcting a pre-generated navigation path for an autonomous vehicle.

Documents

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Application documents
1 201741034784-STATEMENT OF UNDERTAKING (FORM 3) [29-09-2017(online)].pdf 29 Sep 2017
2 201741034784-REQUEST FOR EXAMINATION (FORM-18) [29-09-2017(online)].pdf 29 Sep 2017
3 201741034784-POWER OF AUTHORITY [29-09-2017(online)].pdf 29 Sep 2017
4 201741034784-FORM 18 [29-09-2017(online)].pdf 29 Sep 2017
5 201741034784-FORM 1 [29-09-2017(online)].pdf 29 Sep 2017
6 201741034784-DRAWINGS [29-09-2017(online)].pdf 29 Sep 2017
7 201741034784-DECLARATION OF INVENTORSHIP (FORM 5) [29-09-2017(online)].pdf 29 Sep 2017
8 201741034784-COMPLETE SPECIFICATION [29-09-2017(online)].pdf 29 Sep 2017
9 201741034784-REQUEST FOR CERTIFIED COPY [02-10-2017(online)].pdf 02 Oct 2017
10 abstract 201741034784.jpg 03 Oct 2017
11 201741034784-REQUEST FOR CERTIFIED COPY [20-12-2017(online)].pdf 20 Dec 2017
12 201741034784-Proof of Right (MANDATORY) [20-12-2017(online)].pdf 20 Dec 2017
13 Correspondence by Agent_Form30,Form1_26-12-2017.pdf 26 Dec 2017
14 201741034784-REQUEST FOR CERTIFIED COPY [08-02-2018(online)].pdf 08 Feb 2018
15 201741034784-RELEVANT DOCUMENTS [02-02-2021(online)].pdf 02 Feb 2021
16 201741034784-PETITION UNDER RULE 137 [02-02-2021(online)].pdf 02 Feb 2021
17 201741034784-Information under section 8(2) [02-02-2021(online)].pdf 02 Feb 2021
18 201741034784-FORM 3 [02-02-2021(online)].pdf 02 Feb 2021
19 201741034784-OTHERS [03-02-2021(online)].pdf 03 Feb 2021
20 201741034784-FER_SER_REPLY [03-02-2021(online)].pdf 03 Feb 2021
21 201741034784-DRAWING [03-02-2021(online)].pdf 03 Feb 2021
22 201741034784-CORRESPONDENCE [03-02-2021(online)].pdf 03 Feb 2021
23 201741034784-CLAIMS [03-02-2021(online)].pdf 03 Feb 2021
24 201741034784-FER.pdf 17 Oct 2021
25 201741034784-US(14)-HearingNotice-(HearingDate-18-08-2022).pdf 03 Aug 2022
26 201741034784-POA [13-08-2022(online)].pdf 13 Aug 2022
27 201741034784-FORM 13 [13-08-2022(online)].pdf 13 Aug 2022
28 201741034784-Correspondence to notify the Controller [13-08-2022(online)].pdf 13 Aug 2022
29 201741034784-AMENDED DOCUMENTS [13-08-2022(online)].pdf 13 Aug 2022
30 201741034784-Written submissions and relevant documents [29-08-2022(online)].pdf 29 Aug 2022
31 201741034784-PatentCertificate01-09-2022.pdf 01 Sep 2022
32 201741034784-IntimationOfGrant01-09-2022.pdf 01 Sep 2022
33 201741034784-FORM-27 [28-09-2026(online)].pdf 28 Sep 2026
34 201741034784-FORM-27 [28-09-2026(online)]-2.pdf 28 Sep 2026
35 201741034784-FORM-27 [28-09-2026(online)]-1.pdf 28 Sep 2026
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