A Path Planning Method with a Bidirectional Potential Field Probabilistic Step Size RRT for a Dual Manipulator
Author:
Liu Youyu123ORCID, Tao Wanbao13, Li Shunfang2, Li Yi13, Wang Qijie13
Affiliation:
1. Anhui Key Laboratory of Detection Technology and Energy Saving Devices, Anhui Polytechnic University, Wuhu 241000, China 2. Research Office, Wuhu Institute of Technology, Wuhu 241000, China 3. Mechanical Engineering Department, Anhui Polytechnic University, Wuhu 241000, China
Abstract
The search efficiency of a rapidly exploring random tree (RRT) can be improved by introducing a high-probability goal bias strategy. In the case of multiple complex obstacles, the high-probability goal bias strategy with a fixed step size will fall into a local optimum, which reduces search efficiency. Herein, a bidirectional potential field probabilistic step size rapidly exploring random tree (BPFPS-RRT) was proposed for the path planning of a dual manipulator by introducing a search strategy of a step size with a target angle and random value. The artificial potential field method was introduced, combining the search features with the bidirectional goal bias and the concept of greedy path optimization. According to simulations, taking the main manipulator as an example, compared with goal bias RRT, variable step size RRT, and goal bias bidirectional RRT, the proposed algorithm reduces the search time by 23.53%, 15.45%, and 43.78% and decreases the path length by 19.35%, 18.83%, and 21.38%, respectively. Moreover, taking the slave manipulator as another example, the proposed algorithm reduces the search time by 6.71%, 1.49%, and 46.88% and decreases the path length by 19.88%, 19.39%, and 20.83%, respectively. The proposed algorithm can be adopted to effectively achieve path planning for the dual manipulator.
Funder
Open Research Fund of the Anhui Key Laboratory of Detection Technology and Energy Saving Devices Enterprise Cooperation Projects from Anhui Institute of Future Technologies Innovation and Entrepreneurship Training Program for College Students
Subject
Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry
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