运动规划
移动机器人
机器人
计算机科学
随机树
路径(计算)
数学优化
非完整系统
实时计算
模拟
控制理论(社会学)
人工智能
数学
控制(管理)
程序设计语言
标识
DOI:10.1109/icsse55923.2022.9948258
摘要
It is inevitable for a mobile robot to competently plan an optimal path from its starting, or current, location to a desired goal location. This is an insignificant task when the environment is unvarying. However, the practicable environment for the robot is hardly static, and it often has many moving obstacles. The robot may encounter one, or many, of these unknown and unforeseeable dynamic obstacles. The robot will now opt to proceed, when one of these obstacles is obstructing its path. The objective of this paper is to find a reasonable relation between parameters used in the path planning algorithm in a platform which a robot will be able to move from the start point in a dynamic environment with map and plan an optimal path to specified goal without any collision with moving and static obstacles. For this purpose, an asymptotically optimal version of Rapidly-exploring Random Tree (RRT algorithm), named RRT* is used. The algorithm is based on an incremental sampling which covers the whole space and acts fast. Moreover, this algorithm is computationally efficient, therefore it can be used in multidimensional environments.A method of dynamic replanning using TD-RRT* is presented. The robot will rectify or modify its path when unknown random moving or static snag obstructs the path. Various experimental results show the effectiveness of the proposed method which is faster than the basic RRT*, and the smooth path with the shortest distance can be obtained which satisfies the nonholonomic constraint of mobile robots.
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