Path planning of RRT-Connect robotic arm based on Beetle Antennae algorithm

Aiming at the problems of large randomness, many redundant nodes, and long search time in path planning of the RRT-Connect algorithm in searching, an improved RRT-Connect algorithm was proposed. Improve search efficiency by adding a third point between the start and end point as a new extension point. Combined with the Beetle Antennae Search algorithm, the smell concentration capability sensed by the left and right antennae of the Beetle Antennae Search algorithm is brought into RRT-Connect to reduce the number of redundant points and accelerate the convergence speed. Simulation experiments of the original and improved RRT-Connect algorithm are carried out in 2D and 3D environments respectively, and the experiments show that it can effectively shorten the path length and reduce the search time. Finally, the effectiveness of the improved algorithm is verified by the simulation of the robotic arm.

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Publication Details

Published
2024-12-27
DOI
https://doi.org/10.1109/icairc64177.2024.10899938
Primary Topic
Robotic Path Planning Algorithms
Type
article
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article

Path planning of RRT-Connect robotic arm based on Beetle Antennae algorithm

Xiangde Liu, Fei Jiang
Robotic Path Planning Algorithms
article

Path planning of RRT-Connect robotic arm based on Beetle Antennae algorithm

Xiangde Liu, Fei Jiang
article en

Abstract

Aiming at the problems of large randomness, many redundant nodes, and long search time in path planning of the RRT-Connect algorithm in searching, an improved RRT-Connect algorithm was proposed. Improve search efficiency by adding a third point between the start and end point as a new extension point. Combined with the Beetle Antennae Search algorithm, the smell concentration capability sensed by the left and right antennae of the Beetle Antennae Search algorithm is brought into RRT-Connect to reduce the number of redundant points and accelerate the convergence speed. Simulation experiments of the original and improved RRT-Connect algorithm are carried out in 2D and 3D environments respectively, and the experiments show that it can effectively shorten the path length and reduce the search time. Finally, the effectiveness of the improved algorithm is verified by the simulation of the robotic arm.

Chongqing University of Posts and Telecommunications (CN)
Openalex Percentile: Top 72%
Robotic Path Planning Algorithms
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