基于势场法的无人车局部动态避障路径规划算法

Translated title of the contribution: Local Dynamic Obstacle Avoidance Path Planning Algorithm for Unmanned Vehicles Based on Potential Field Method

Li Zhai, Xueying Zhang*, Xian Zhang, Chengping Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)

Abstract

To achieve dynamic real-time obstacle avoidance of unmanned vehicles, a local obstacle avoidance path planning algorithm was proposed based on artificial potential field method. Firstly, improving the potential field environment and the potential field force were arranged in the new method to solve the local minimum value and target unreachable problem of the traditional potential field method. And then, considering the safety of vehicle collisions, the working conditions of lateral dynamic obstacles and the same direction dynamic obstacles were analyzed, and a dynamic window method was used for real-time dynamic obstacle avoidance planning. To ensure path flatness and traceability, a BSL curve was used to smoothing the planned path. Finally, the proposed control algorithm was verified under the co-simulation platform of CarSim and Matlab/Simulink. The simulation results show the effectiveness, safety and traceability of the planning algorithm for obstacle avoidance.

Translated title of the contributionLocal Dynamic Obstacle Avoidance Path Planning Algorithm for Unmanned Vehicles Based on Potential Field Method
Original languageChinese (Traditional)
Pages (from-to)696-705
Number of pages10
JournalBeijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume42
Issue number7
DOIs
Publication statusPublished - Jul 2022

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