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

Author(s):  
Jin-Gu Kang ◽  
Dong-Woo Lim ◽  
Yong-Sik Choi ◽  
Woo-Jin Jang ◽  
Jin-Woo Jung

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.

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 333
Author(s):  
Jin-Gu Kang ◽  
Dong-Woo Lim ◽  
Yong-Sik Choi ◽  
Woo-Jin Jang ◽  
Jin-Woo Jung

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.


Author(s):  
Jin-Gu Kang ◽  
Dong-Woo Lim ◽  
Yong-Sik Choi ◽  
Woo-Jin Jang ◽  
Jin-Woo Jung

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.


Author(s):  
Jin-Gu Kang ◽  
Dong-Woo Lim ◽  
Yong-Sik Choi ◽  
Woo-Jin Jang ◽  
Jin-Woo Jung

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.


2021 ◽  
Vol 155 ◽  
pp. 107173
Author(s):  
Meng Zhao ◽  
Hui Lu ◽  
Siyi Yang ◽  
Yinan Guo ◽  
Fengjuan Guo

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