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<p>This research designs a wheeled sweeping robot with autonomous path planning and obstacle avoidance capabilities. The robot uses STM32 as the central processing unit, and is equipped with an encoder and a gyroscope to realize the precise motion control and position. The front infrared sensors array are used to detect obstacles, and realize the function of autonomous obstacle avoidance of the robot. An improved bow-shape algorithm is proposed to realize the cleaning path planning of the robot to improve the coverage of the robot’s motion path. Aiming at the problem of linear deviation of robots and irregular shapes of the obstacles, a multi-stage along-line and dynamic along-edge PID control algorithms are proposed in this research. Finally, experiment was carried out and the results proved that the corner dust removal ability and obstacle avoidance capabilities has been greatly improved than the traditional inertial navigation planning algorithm, and the coverage rate of the robot’s moving path is increased by 6.22%.</p>

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Path planning and controlling of wheeled sweeping robot based on inertial navigation

  • 期刊论文

  • 发表日期：

    2025年12月29日

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  • Haichu Chen,
  • Ke Li,
  • Nianlong Pan,
  • Jierong He

摘要

This research designs a wheeled sweeping robot with autonomous path planning and obstacle avoidance capabilities. The robot uses STM32 as the central processing unit, and is equipped with an encoder and a gyroscope to realize the precise motion control and position. The front infrared sensors array are used to detect obstacles, and realize the function of autonomous obstacle avoidance of the robot. An improved bow-shape algorithm is proposed to realize the cleaning path planning of the robot to improve the coverage of the robot’s motion path. Aiming at the problem of linear deviation of robots and irregular shapes of the obstacles, a multi-stage along-line and dynamic along-edge PID control algorithms are proposed in this research. Finally, experiment was carried out and the results proved that the corner dust removal ability and obstacle avoidance capabilities has been greatly improved than the traditional inertial navigation planning algorithm, and the coverage rate of the robot’s moving path is increased by 6.22%.