FHQ-RRT: An Improved Path Planning Algorithm for Mobile Robots to Acquire High-Quality Paths Faster

• Published in: Sensors (Basel, Switzerland) Vol. 25; no. 7; p. 2189
• Main Authors: Dong, Xingxiang, Wang, Yujun, Fang, Can, Ran, Kemeng, Liu, Guohui
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 30.03.2025; MDPI
• Subjects: Autonomous vehicles; Efficiency; Genetic algorithms; Methods; optimal path planning; Optimization; path planning; Planning; rapidly explored random tree; Robots; sampling-based algorithms; Sensors; optimal path planning; sampling-based algorithms; path planning; rapidly explored random tree

The Rapidly-exploring Random Tree Star (RRT*) algorithm, widely utilized for path planning, faces challenges, such as slow acquisition of feasible paths and high path costs. To address this issue, this paper presents an improved algorithm based on RRT* that can obtain high-quality paths faster, term...