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.
| Original language | English |
|---|---|
| Pages (from-to) | 24-35 |
| Number of pages | 12 |
| Journal | Journal of Shanghai Jiaotong University (Science) |
| Volume | 27 |
| Issue number | 1 |
| DOIs | |
| State | Published - Feb 2022 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- 3D grids
- A
- TP 242.3
- TP 391
- automated dispensing medicines
- dynamic obstacle avoidance
- dynamic unstructured environment
- human-robot collaboration
- multi-sensor depth images
- reactive control method
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