Collision-free human-robot collaboration based on context awareness

Recent advancements in human-robot collaboration have enabled human operators and robots to work together in a shared manufacturing environment. However, current distance-based collision-free human-robot collaboration system can only ensure human safety but not assembly efficiency. In this paper, the authors present a context awareness-based collision-free human-robot collaboration system that can provide human safety and assembly efficiency at the same time. The system can plan robotic paths that avoid colliding with human operators while still reach target positions in time. Human operators' poses can also be recognised with low computational expenses to further improve assembly efficiency. To support the context-aware collision-free system, a complete collision sensing module with sensor calibration algorithms is proposed and implemented. An efficient transfer learning-based human pose recognition algorithm is also adapted and tested. Two experiments are designed to test the performance of the proposed human pose recognition algorithm and the overall system. The results indicate an efficiency improvement of the overall system.

Automated summary

Recent advancements in human-robot collaboration have led to the development of a context awareness-based collision-free system that ensures both human safety and assembly efficiency. This system can plan robotic paths to avoid collisions with human operators while reaching target positions in a timely manner, and can also recognize human operators' poses with low computational costs to further improve assembly efficiency. The system incorporates a collision sensing module with sensor calibration algorithms and a transfer learning-based human pose recognition algorithm to enhance overall system performance.