Improved RRT* Path-Planning Algorithm Based on the Clothoid Curve for a Mobile Robot Under Kinematic Constraints

Autor: Kemeng Ran, Yujun Wang, Can Fang, Qisen Chai, Xingxiang Dong, Guohui Liu
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Sensors, Vol 24, Iss 23, p 7812 (2024)
Druh dokumentu: article
ISSN: 1424-8220
DOI: 10.3390/s24237812
Popis: In this paper, we propose an algorithm based on the Rapidly-exploring Random Trees* (RRT*) algorithm for the path planning of mobile robots under kinematic constraints, aiming to generate efficient and smooth paths quickly. Compared to other algorithms, the main contributions of our proposed algorithm are as follows: First, we introduce a bidirectional expansion strategy that quickly identifies a direct path to the goal point in a short time. Second, a node reconnection strategy is used to eliminate unnecessary nodes, thereby reducing the path length and saving memory. Third, a path deformation strategy based on the Clothoid curve is devised to enhance obstacle avoidance and path-planning capability, ensuring collision-free paths that comply with the kinematic constraints of mobile robots. Simulation results demonstrate that our algorithm is simpler, more computationally efficient, expedites pathfinding, achieves higher success rates, and produces smoother paths compared to existing algorithms.
Databáze: Directory of Open Access Journals
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