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Article

Collision-Free Path Planning Method for Robots Based on an Improved Rapidly-Exploring Random Tree Algorithm

1
School of Mechanical Engineering, Beijing Institute of Technology, No. 5 Zhongguancun South Street, Haidian District, Beijing 100081, China
2
School of Computer Science and Technology, Beijing Institute of Technology, No. 5 Zhongguancun South Street, Haidian District, Beijing 100081, China
3
School of Mechatronical Engineering, Beijing Institute of Technology, No. 5 Zhongguancun South Street, Haidian District, Beijing 100081, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(4), 1381; https://doi.org/10.3390/app10041381
Received: 20 January 2020 / Revised: 12 February 2020 / Accepted: 13 February 2020 / Published: 19 February 2020
(This article belongs to the Special Issue Novel Industry 4.0 Technologies and Applications)
Sampling-based methods are popular in the motion planning of robots, especially in high-dimensional spaces. Among the many such methods, the Rapidly-exploring Random Tree (RRT) algorithm has been widely used in multi-degree-of-freedom manipulators and has yielded good results. However, existing RRT planners have low exploration efficiency and slow convergence speed and have been unable to meet the requirements of the intelligence level in the Industry 4.0 mode. To solve these problems, a general autonomous path planning algorithm of Node Control (NC-RRT) is proposed in this paper based on the architecture of the RRT algorithm. Firstly, a method of gradually changing the sampling area is proposed to guide exploration, thereby effectively improving the search speed. In addition, the node control mechanism is introduced to constrain the extended nodes of the tree and thus reduce the extension of invalid nodes and extract boundary nodes (or near-boundary nodes). By changing the value of the node control factor, the random tree is prevented from falling into a so-called “local trap” phenomenon, and boundary nodes are selected as extended nodes. The proposed algorithm is simulated in different environments. Results reveal that the algorithm greatly reduces the invalid exploration in the configuration space and significantly improves planning efficiency. In addition, because this method can efficiently use boundary nodes, it has a stronger applicability to narrow environments compared with existing RRT algorithms and can effectively improve the success rate of exploration. View Full-Text
Keywords: Rapidly-exploring Random Tree (RRT); manipulator; motion planning; obstacle avoidance; complex environment Rapidly-exploring Random Tree (RRT); manipulator; motion planning; obstacle avoidance; complex environment
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MDPI and ACS Style

Wang, X.; Luo, X.; Han, B.; Chen, Y.; Liang, G.; Zheng, K. Collision-Free Path Planning Method for Robots Based on an Improved Rapidly-Exploring Random Tree Algorithm. Appl. Sci. 2020, 10, 1381. https://doi.org/10.3390/app10041381

AMA Style

Wang X, Luo X, Han B, Chen Y, Liang G, Zheng K. Collision-Free Path Planning Method for Robots Based on an Improved Rapidly-Exploring Random Tree Algorithm. Applied Sciences. 2020; 10(4):1381. https://doi.org/10.3390/app10041381

Chicago/Turabian Style

Wang, Xinda; Luo, Xiao; Han, Baoling; Chen, Yuhan; Liang, Guanhao; Zheng, Kailin. 2020. "Collision-Free Path Planning Method for Robots Based on an Improved Rapidly-Exploring Random Tree Algorithm" Appl. Sci. 10, no. 4: 1381. https://doi.org/10.3390/app10041381

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