避障
最大值和最小值
模糊逻辑
计算机科学
运动规划
机器人
障碍物
功能(生物学)
路径(计算)
平滑度
数学优化
控制理论(社会学)
移动机器人
数学
人工智能
控制(管理)
生物
法学
程序设计语言
数学分析
进化生物学
政治学
作者
Ce Xu,Zhenbang Xu,Mingyi Xia
出处
期刊:Applied sciences
[Multidisciplinary Digital Publishing Institute]
日期:2021-01-06
卷期号:11 (2): 504-504
被引量:15
摘要
This paper presents a real-time path planning approach for controlling the motion of space-based robots. The algorithm can plan three-dimensional trajectories for agents in a complex environment which includes numerous static and dynamic obstacles, path constraints, and/or performance constraints. This approach is extended based on the dynamic window approach (DWA). As the classic reactive method for obstacle avoidance, DWA uses an optimized function to select the best motion command. The original DWA optimization function consists of three weight terms. Changing the weights of these terms will change the behavior of the algorithm. In this paper, to improve the evaluation ability of the optimization function and the robot’s ability to adapt to the environment, a new optimization function is designed and combined with fuzzy logic to adjust the weights of each parameter of the optimization function. Given that DWA has the defect of local minima, which makes the robot hard to escape U-shaped obstacles, a dual dynamic window method and local goals are adopted in this article to help the robot escape local minima. By comparison, the proposed method is superior to traditional DWA and fuzzy DWA (F_DWA) in terms of computational efficiency, smoothness and security.
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