Rapidly Exploring Random Tree- back (RRT-Back)

This paper proposes a backtracking Rapidly Exploring Random Tree (RRT-Back) algorithm to reduce the length of the generated path.The proposed algorithm enhances path optimization by employing path backtracking to eliminate redundant nodes and utilizing direct linear connections between discontinuous nodes to shorten path length.To minimize computational expense, the method incorporates cost-effective connections within the already generated path, following the principles of the RRT algorithm.The experimental results demonstrate that the RRT-Back algorithm significantly enhances the feasibility and efficiency of paths in complex environments.

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Publication Details

Journal
Proceedings of International Conference on Artificial Life and Robotics
Published
2025-02-13
DOI
https://doi.org/10.5954/icarob.2025.os3-2
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Rapidly Exploring Random Tree- back (RRT-Back)

Miao Zhang, Jingyang Gao
Proceedings of International Conference on Artificial Life and Robotics
Cell Image Analysis Techniques
article

Rapidly Exploring Random Tree- back (RRT-Back)

Miao Zhang, Jingyang Gao
article en

Abstract

This paper proposes a backtracking Rapidly Exploring Random Tree (RRT-Back) algorithm to reduce the length of the generated path.The proposed algorithm enhances path optimization by employing path backtracking to eliminate redundant nodes and utilizing direct linear connections between discontinuous nodes to shorten path length.To minimize computational expense, the method incorporates cost-effective connections within the already generated path, following the principles of the RRT algorithm.The experimental results demonstrate that the RRT-Back algorithm significantly enhances the feasibility and efficiency of paths in complex environments.

Proceedings of International Conference on Artificial Life and RoboticsVol. 30
Tianjin University of Science and Technology (CN)
Openalex Percentile: Top 60%
Cell Image Analysis Techniques
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