Light Reflection-Guided RRT${*}$: Efficient Path Planning in Narrow Passages
Xiaotong Xun, Runda Zhang, Senchun Chai, Runqi Chai, Yuanqing Xia
Abstract
In complex and constrained environments, robot path planning faces the dual challenges of efficiency and solution quality. This paper presents a Light Reflection Heuristic RRT<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^*$</tex-math></inline-formula> algorithm (LRH-RRT<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^*$</tex-math></inline-formula>), which generates the reference path by simulating light reflections along obstacle boundaries and adaptively adjusts the sampling distribution. A dynamic path pruning strategy is introduced to eliminate redundant nodes, and third-order Bézier curve interpolation is applied to smooth the path while satisfying the dynamic constraints of mobile robots. Experimental results demonstrate that LRH-RRT<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^*$</tex-math></inline-formula> improves planning efficiency and path quality in various narrow passage scenarios.
BibTeX
@inproceedings{ral2025_lightreflectiong,
title = {Light Reflection-Guided RRT${*}$: Efficient Path Planning in Narrow Passages},
author = {Xiaotong Xun and Runda Zhang and Senchun Chai and Runqi Chai and Yuanqing Xia},
booktitle = {RA-L 2025},
year = {2025}
}