运动规划
障碍物
卡西姆
势场
避障
路径(计算)
控制器(灌溉)
计算机科学
边界(拓扑)
领域(数学)
控制理论(社会学)
模拟
MATLAB语言
控制工程
工程类
人工智能
移动机器人
数学
机器人
控制(管理)
数学分析
地质学
程序设计语言
法学
纯数学
操作系统
地球物理学
生物
政治学
农学
作者
Zhixian Liu,Xiaofang Yuan,Guoming Huang,Yaonan Wang,Xizheng Zhang
标识
DOI:10.1016/j.isatra.2020.12.015
摘要
Path planning is a basic function for autonomous vehicle (AV). However, it is difficult to adapt to different velocities and different types of obstacles including dynamic obstacle and static obstacle (such as road boundary) for AV. To solve the problem of path planning under different velocities and different types of obstacles, a two potential fields fused adaptive path planning system (TPFF-APPS) which includes two parts, a potential field fusion controller and an adaptive weight assignment unit, is presented in this work. In the potential field fusion controller, a novel potential velocity field is built by velocity information and fused with a traditional artificial potential field for adapting various velocities. The adaptive weight assignment unit is designed to distribute adaptively the weights of two potential fields for adapting different types of obstacles at the same time, including road boundary and dynamic obstacles. The simulation is carried on the Carsim-Matlab co-simulation platform, and the simulation results indicate that the proposed TPFF-APPS has excellent performance for path planning adapting to different velocities and different types of obstacles.
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