Collision-free human-robot collaboration based on context awareness

被引:85
|
作者
Liu, Hongyi [1 ]
Wang, Lihui [1 ]
机构
[1] KTH Royal Inst Technol, Dept Prod Engn, Stockholm, Sweden
关键词
Human-robot collaboration; Collision-free system; Context awareness; Deep learning; SAFETY; CALIBRATION; AVOIDANCE; DRIVEN; MODEL;
D O I
10.1016/j.rcim.2020.101997
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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.
引用
收藏
页数:9
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