US 11,656,627 B2
Open space path planning using inverse reinforcement learning
Jinyun Zhou, Sunnyvale, CA (US); Qi Luo, Sunnyvale, CA (US); Shu Jiang, Sunnyvale, CA (US); Jiaming Tao, Sunnyvale, CA (US); Yu Wang, Sunnyvale, CA (US); Jiaxuan Xu, Sunnyvale, CA (US); Kecheng Xu, Sunnyvale, CA (US); Jinghao Miao, Sunnyvale, CA (US); and Jiangtao Hu, Sunnyvale, CA (US)
Assigned to BAIDU USA LLC, Sunnyvale, CA (US)
Filed by Baidu USA LLC, Sunnyvale, CA (US)
Filed on Mar. 23, 2020, as Appl. No. 16/827,452.
Prior Publication US 2021/0294340 A1, Sep. 23, 2021
Int. Cl. G05D 1/02 (2020.01); G05D 1/00 (2006.01)
CPC G05D 1/0221 (2013.01) [G05D 1/0088 (2013.01); G05D 1/0217 (2013.01); G05D 2201/0212 (2013.01); G05D 2201/0213 (2013.01)] 20 Claims
OG exemplary drawing
15. A data processing system, comprising:
a processor; and
a memory coupled to the processor to store instructions, which when executed by the processor, cause the processor to perform operations, the operations including
determining a route for an autonomous driving vehicle (ADV) from a first location of the ADV to a second location within an open space, the first location being a current location of the ADV;
determining an objective function based on the route, the objective function having a set of costs for maneuvering the ADV from the first location to the second location;
performing a table lookup into a table that associates weights with environmental conditions using on one or more environmental conditions of the open space to determine a set of weights, wherein at least some of the weights represent behaviors of expert drivers with respect to at least one environmental condition, wherein each weight of the set of weights is to be applied to a corresponding cost of the objective function;
optimizing the objective function in view of one or more constraints, such that an output of the objective function reaches minimum while the one or more constraints are satisfied; and
generating a path trajectory with the optimized objective function to control the ADV autonomously along the path trajectory.