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

• Published in: Sensors (Basel, Switzerland) Vol. 24; no. 23; p. 7812
• Main Authors: Ran, Kemeng, Wang, Yujun, Fang, Can, Chai, Qisen, Dong, Xingxiang, Liu, Guohui
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 06.12.2024; MDPI
• Subjects: Algorithms; Clothoid curve; Comparative analysis; Deep learning; Efficiency; Genetic algorithms; Kinematics; obstacle avoidance; Optimization algorithms; path planning; Planning; Robotics; Robots; RRT; obstacle avoidance; path planning; Clothoid curve; RRT
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s24237812

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.