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.
WANG Zheng (王正), XU Hui (许辉), L v Na (吕娜), TAO Wei∗ (陶卫),
CHEN Guodong (陈国栋), CHI Wenzheng (迟文正), SUN Lining (孙立宁)
. Dynamic Obstacle Avoidance for Application of Human-Robot Cooperative Dispensing Medicines[J]. Journal of Shanghai Jiaotong University(Science), 2022
, 27(1)
: 24
-35
.
DOI: 10.1007/s12204-021-2366-5
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