The Navigation of Mobile Robot in the Indoor Dynamic Unknown Environment Based on Decision Tree Algorithm.

Journal: Computational intelligence and neuroscience
Published Date: Jun 20, 2022

Abstract

This study proposes an optimized algorithm for the navigation of the mobile robot in the indoor and dynamic unknown environment based on the decision tree algorithm. Firstly, the error of the yaw value outputted from IMU sensor fusion module is analyzed in the indoor environment; then, the adaptive FAST SLAM is proposed to optimize the yaw value from the odometer; in the next, a decision tree algorithm is applied which predicts the correct moving direction of the mobile robot through the outputted yaw value from the IMU sensor fusion module and adaptive FAST SLAM of the odometer data in the indoor and dynamic environment; the following is the navigation algorithm proposed for the mobile robot in the dynamic and unknown environment; finally, a real mobile robot is designed to verify the proposed algorithm.The final result shows the proposed algorithms are valid and effective.

Authors

  • Yupei Yan
    Department of Artificial Intelligence, Zhuhai City Polytechnic College, Zhuhai 519090, China.
  • Weimin Ma
    Department of Artificial Intelligence, Zhuhai City Polytechnic College, Zhuhai 519090, China.
  • Yangmin Li
    Department of Industrial and Systems Engineering, HongKong Polytechnic University, HongKong 999077, Hong Kong.
  • Sengfat Wong
    Faculty of Science and Technology, University of Macau, Macau 999078, Macau.
  • Ping He
    Shanghai Hospital Development Center, Shanghai 200040, China. Electronic address: heping@shdc.org.cn.
  • Shaoping Zhu
    Department of Artificial Intelligence, Zhuhai City Polytechnic College, Zhuhai 519090, China.
  • Xuemei Yin
    Department of Artificial Intelligence, Zhuhai City Polytechnic College, Zhuhai 519090, China.

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