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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2021, Vol. 42 ›› Issue (4): 524909-524909.doi: 10.7527/S1000-6893.2020.24909

• Electronics and Electrical Engineering and Control • Previous Articles     Next Articles

A pedestrian-aware collision-free following approach for mobile robots based on A* and TEB

PANG Lei1,2, CAO Zhiqiang1,2, YU Junzhi1,3   

  1. 1. State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China;
    2. School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China;
    3. Department of Advanced Manufacturing and Robotics, College of Engineering, Peking University, Beijing 100871, China
  • Received:2020-10-21 Revised:2020-11-12 Published:2020-11-27
  • Supported by:
    National Natural Science Foundation of China (61633020, 61633017, 61725305, 61836015)

Abstract: Navigation by following a specified leader is a convenient way for mobile robots. To solve the problem of robot’s following with obstacle avoidance, a collision-free following approach based on path planning is proposed. The static obstacle cost map is generated according to the results of the point cloud segmentation. Multiple disturbing pedestrians are tracked based on the Unscented Kalman Filter (UKF) and Nearest Near Joint Probabilistic Data Association (NN-JPDA) to estimate their motion states, and then the dynamic pedestrian cost map is generated. On this basis, the A*-based global planner plans a global path with the static obstacle cost map, whereas the local planner implemented with Timed-Elastic-Band (TEB) algorithm also takes the dynamic pedestrian cost map into account to plan an optimized local path. This local path tends to follow the global path and helps the mobile robot achieve pedestrian-aware obstacle avoidance. By combining low-frequency global planning with high-frequency local planning, the mobile robot realizes a safe and collision-free person following. The effectiveness of the proposed approach is validated by experiments.

Key words: navigation, person following, path planning, obstacle avoidance, motion estimation, collision-free following

CLC Number: