A Distributed Motion Planning Method based on Routing and Local Dynamic Programming
Wen Cheng, Tianyun Gao, Zhongze Liu, Shengfei Li, Ning Li, Lu Caixia · 2020 3rd International Conference on Unmanned Systems (ICUS) · 2020
In this paper, a distributed motion planner based on routing and local dynamic programming is proposed. First, the routing planner generates a high-level reference based on the road segments and zones defined in the Road Network Definition File (RNDF). Then the physical and logical structure of the environment is used to construct a uniform sampling space along the reference, in which a feasible trajectory is grown by numerous incremental sampling points. Finally, a smooth trajectory that meets kinematic constraints in the dynamic and uncertain environment is efficiently generated by use of forward simulation of the vehicle-controller system. In this paper, both the safety and comfort are considered to meet the driving experience, and a recursive function is used to make the trajectory search easier and faster. The proposed motion planner is implemented and tested on a real unmanned vehicle in three different scenarios, and the results show that the framework can output high-quality trajectories to guide the vehicle to its destination safely.