J Shanghai Jiaotong Univ Sci ›› 2022, Vol. 27 ›› Issue (1): 24-35.doi: 10.1007/s12204-021-2366-5

• Robotics & AI in Interdisciplinary Medicine and Engineering • Previous Articles     Next Articles

Dynamic Obstacle Avoidance for Application of Human-Robot Cooperative Dispensing Medicines

WANG Zheng1 (王正), XU Hui2 (许辉), Lv Na3 (吕娜), TAO Wei3∗ (陶卫), CHEN Guodong2 (陈国栋), CHI Wenzheng2∗ (迟文正), SUN Lining2 (孙立宁)   

  1. (1. Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai 200233, China; 2. School of Mechanical and Electrical Engineering; Jiangsu Provincial Key Laboratory of Advanced Robotics; Collaborative Innovation Center of Suzhou Nano Science and Technology, Soochow University, Suzhou 215123, Jiangsu, China; 3. Department of Instrument Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China)
  • Received:2021-04-25 Online:2022-01-28 Published:2022-01-14

Abstract: For safety reasons, in the automated dispensing medicines process, robots and humans cooperate to accomplish the task of drug sorting and distribution. In this dynamic unstructured environment, such as a humanrobot collaboration scenario, the safety of human, robot, and equipment in the environment is paramount. In this work, a practical and effective robot motion planning method is proposed for dynamic unstructured environments. To figure out the problems of blind zones of single depth sensor and dynamic obstacle avoidance, we first propose a method for establishing offline mapping and online fusion of multi-sensor depth images and 3D grids of the robot workspace, which is used to determine the occupation states of the 3D grids occluded by robots and obstacles and to conduct real-time estimation of the minimum distance between the robot and obstacles. Then, based on the reactive control method, the attractive and repulsive forces are calculated and transformed into robot joint velocities to avoid obstacles in real time. Finally, the robot’s dynamic obstacle avoidance ability is evaluated on an experimental platform with a UR5 robot and two KinectV2 RGB-D sensors, and the effectiveness of the proposed method is verified.

Key words: automated dispensing medicines, dynamic unstructured environment, human-robot collaboration, dynamic obstacle avoidance, multi-sensor depth images, 3D grids, reactive control method

CLC Number: