scholarly journals Improved RRT-Connect Algorithm Based on Triangular Inequality for Robot Path Planning

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 333
Author(s):  
Jin-Gu Kang ◽  
Dong-Woo Lim ◽  
Yong-Sik Choi ◽  
Woo-Jin Jang ◽  
Jin-Woo Jung
Keyword(s):  
Path Planning ◽  
Path Length ◽  
Experimental Results ◽  
Random Tree ◽  
Robot Path Planning ◽  
Planning Time ◽  
Triangular Inequality ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Robot Path

This paper proposed a triangular inequality-based rewiring method for the rapidly exploring random tree (RRT)-Connect robot path-planning algorithm that guarantees the planning time compared to the RRT algorithm, to bring it closer to the optimum. To check the proposed algorithm’s performance, this paper compared the RRT and RRT-Connect algorithms in various environments through simulation. From these experimental results, the proposed algorithm shows both quicker planning time and shorter path length than the RRT algorithm and shorter path length than the RRT-Connect algorithm with a similar number of samples and planning time.

scholarly journals Improved RRT-Connect Algorithm Based on Triangular Inequality for Robot Path Planning

2020 ◽  
Author(s):  
Jin-Gu Kang ◽  
Dong-Woo Lim ◽  
Yong-Sik Choi ◽  
Woo-Jin Jang ◽  
Jin-Woo Jung
Keyword(s):  
Path Planning ◽  
Path Length ◽  
Experimental Results ◽  
Random Tree ◽  
Robot Path Planning ◽  
Planning Time ◽  
Triangular Inequality ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Robot Path

This paper proposed a triangular inequality-based rewiring method for the Rapidly exploring Random Tree (RRT)-Connect robot path-planning algorithm that guarantees the planning time compared to the RRT algorithm, to bring it closer to the optimum. To check the proposed algorithm’s performance, this paper compared the RRT and RRT-Connect algorithms in various environments through simulation. From these experimental results, the proposed algorithm shows both quicker planning time and shorter path length than the RRT algorithm and shorter path length than the RRT-Connect algorithm with a similar number of samples and planning time.

scholarly journals Improved RRT-Connect Algorithm Based on Triangular Inequality for Robot Path Planning

2020 ◽  
Author(s):  
Jin-Gu Kang ◽  
Dong-Woo Lim ◽  
Yong-Sik Choi ◽  
Woo-Jin Jang ◽  
Jin-Woo Jung
Keyword(s):  
Path Planning ◽  
Path Length ◽  
Experimental Results ◽  
Random Tree ◽  
Robot Path Planning ◽  
Planning Time ◽  
Triangular Inequality ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Robot Path

This paper proposed a triangular inequality-based rewiring method for the Rapidly exploring Random Tree (RRT)-Connect robot path-planning algorithm that guarantees the planning time compared to the RRT algorithm, to bring it closer to the optimum. To check the proposed algorithm’s performance, this paper compared the RRT and RRT-Connect algorithms in various environments through simulation. From these experimental results, the proposed algorithm shows both quicker planning time and shorter path length than the RRT algorithm and shorter path length than the RRT-Connect algorithm with a similar number of samples and planning time.

scholarly journals On the Enhancement of Optimality in the RRT-Connect Robot Path Planning Algorithm

2020 ◽  
Author(s):  
Jin-Gu Kang ◽  
Dong-Woo Lim ◽  
Yong-Sik Choi ◽  
Woo-Jin Jang ◽  
Jin-Woo Jung
Keyword(s):  
Path Planning ◽  
Experimental Results ◽  
Random Tree ◽  
Convergence Time ◽  
Robot Path Planning ◽  
Triangular Inequality ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Robot Path

This paper proposed a Triangular Inequality based rewiring method for the RRT(Rapidly exploring Random Tree)-Connect robot path planning algorithm that guarantees the convergence time than the RRT algorithm, to enhance the optimality. To check the performance of the proposed algorithm, this paper compared with the RRT and RRT-Connect algorithms in various environments through simulation. From these experimental results, the proposed algorithm shows both quick convergence time and better optimality than the RRT algorithm, and more optimal than RRT-Connect algorithm with the similar number of sampling and convergence time.

scholarly journals An Enhancement Method of Rapidly-exploring Random Tree Robot Path Planning using Midpoint Interpolation

2021 ◽  
Author(s):  
Jin-Gu Kang ◽  
Yong-Sik Choi ◽  
Jin-Woo Jung
Keyword(s):  
Path Planning ◽  
Path Length ◽  
Interpolation Method ◽  
Optimal Path ◽  
Random Tree ◽  
Interpolation Process ◽  
Robot Path Planning ◽  
Planning Time ◽  
Enhancement Method ◽  
Robot Path

To solve the problem that sampling-based Rapidly-exploring Random Tree (RRT) method is difficult to guarantee optimality. This paper proposed the Post Triangular Processing of Midpoint Interpolation method minimized the planning time and shorter path length of the sampling-based algorithm. The proposed Post Triangular Processing of Midpoint Interpolation method makes a closer to the optimal path and somewhat solves the sharp path problem through the interpolation process. The experiments were conducted to verify the performance of the proposed method. Applying the method proposed in this paper to the RRT algorithm increases the efficiency of optimization compared to the planning time.

scholarly journals A Method of Enhancing Rapidly-Exploring Random Tree Robot Path Planning Using Midpoint Interpolation

2021 ◽  
Vol 11 (18) ◽  
pp. 8483
Author(s):  
Jin-Gu Kang ◽  
Yong-Sik Choi ◽  
Jin-Woo Jung
Keyword(s):  
Path Planning ◽  
Path Length ◽  
Interpolation Method ◽  
Optimal Path ◽  
Random Tree ◽  
Interpolation Process ◽  
Robot Path Planning ◽  
Planning Time ◽  
Robot Path

It is difficult to guarantee optimality using the sampling-based rapidly-exploring random tree (RRT) method. To solve the problem, this paper proposes the post triangular processing of the midpoint interpolation method to minimize the planning time and shorten the path length of the sampling-based algorithm. The proposed method makes a path that is closer to the optimal path and somewhat solves the sharp path problem through the interpolation process. Experiments were conducted to verify the performance of the proposed method. Applying the method proposed in this paper to the RRT algorithm increases the efficiency of optimization by minimizing the planning time.

A fast robot path planning algorithm based on bidirectional associative learning

2021 ◽  
Vol 155 ◽  
pp. 107173
Author(s):  
Meng Zhao ◽  
Hui Lu ◽  
Siyi Yang ◽  
Yinan Guo ◽  
Fengjuan Guo
Keyword(s):  
Path Planning ◽  
Associative Learning ◽  
Robot Path Planning ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Robot Path
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