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This study investigates the path planning and tracking problem for wheeled mobile robots (WMR) which describes by nonholonomic lagrange dynamics. Firstly, an integrated coordination path planning algorithm (PGP) combines Particle Swarm Optimization (PSO) for global optimal path generation and Grey Wolf Optimizer (GWO) for local obstacle avoidance refinement. Then, the optimized path is subsequently smoothed using cubic spline interpolation. Nextly, a tracking torque control law tailored for WMR is designed by backstepping methodology and sliding mode control approach. The stable of the closed loop system is guaranteed by Lyapunov-like stable theory. The effectiveness of the proposed approach are comprehensively validated via numerical simulations and path planning and tracking control physical experiments.

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Wheeled Mobile Robot Path Planning and Tracking Control by Integrated Coordination Architecture

  • 会议论文

  • 发表日期：

    2026年

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  • Wencheng Liu,
  • Tenghui Li,
  • Lixia Liu,
  • Rongwei Guo,
  • Bin Li,
  • Yu Zhang,
  • Jinghui Li

摘要

This study investigates the path planning and tracking problem for wheeled mobile robots (WMR) which describes by nonholonomic lagrange dynamics. Firstly, an integrated coordination path planning algorithm (PGP) combines Particle Swarm Optimization (PSO) for global optimal path generation and Grey Wolf Optimizer (GWO) for local obstacle avoidance refinement. Then, the optimized path is subsequently smoothed using cubic spline interpolation. Nextly, a tracking torque control law tailored for WMR is designed by backstepping methodology and sliding mode control approach. The stable of the closed loop system is guaranteed by Lyapunov-like stable theory. The effectiveness of the proposed approach are comprehensively validated via numerical simulations and path planning and tracking control physical experiments.