Robot Differential Drive Navigation Through Probabilistic Roadmap and Pure Pursuit

作     者：Ali, Maram Das, Saptarshi Townley, Stuart 

作者机构：Univ Exeter Fac Environm Sci & Econ Ctr Environm Math Penryn Campus Penryn TR10 9FE Cornwall England King Khalid Univ Coll Sci Dept Math Abha 62223 Saudi Arabia Univ Exeter Inst Data Sci & Artificial Intelligence Exeter EX4 4QE Devon England Univ Exeter Environm & Sustainabil Inst Penryn Campus Penryn TR10 9FE Cornwall England 

出 版 物：《IEEE ACCESS》 (IEEE Access)

年 卷 期：2025年第13卷

页      面：22118-22132页

核心收录：

基　　金：King Khalid University Saudi Arabia Cultural Bureau in U.K 

主　　题：Robots Navigation Path planning Planning Real-time systems Kinematics Mobile robots Heuristic algorithms Pursuit algorithms Wheels Differential drive navigation probabilistic roadmap pure pursuit path planning unexplored terrains 

摘      要：This research addresses autonomous navigation for differential drive robots by integrating probabilistic roadmap (PRM) and pure pursuit algorithms. The proposed method innovatively tackles path planning challenges in complex environments by developing a novel framework that combines forward kinematics, binary occupancy mapping, and adaptive path generation. The approach demonstrates superior navigation performance through efficient path planning in constrained spaces, validated by a case study in Riyadh, Saudi Arabia. By using PRM s probabilistic path generation and pure pursuit s real-time control, the method outperforms traditional navigation techniques in generating feasible trajectories through intricate environments. Key contributions include a comprehensive framework for robot navigation that offers enhanced adaptability and robust path planning. While being limited to static environments, the research provides a foundational approach for developing more resilient autonomous robotic systems, setting the stage for future navigation algorithm advancements.