A Mixed-Reality-Augmented Deep Reinforcement Learning Approach for Multi-Robot Safe Motion Generation in Human-Robot Collaborative Manufacturing Cells

Augmenting capabilities of human operators with multi-robot cells offers substantial advantages for increasing productivity in manufacturing applications. This synergy effectively combines the strengths of both robots and humans, maximizing operational efficiency and leveraging human capabilities. H...

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Vydané v:	IEEE transactions on automation science and engineering Ročník 22; s. 21033 - 21046
Hlavní autori:	Li, Chengxi, Yin, Yue, Ye, Hantao, Zheng, Pai, Gupta, Satyandra K.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	IEEE 2025
Predmet:	Collaboration Collision avoidance deep reinforcement learning Human-multi-robot collaboration Manufacturing mixed reality Monitoring Real-time systems Robot kinematics Robot motion Robots safe motion generation smart manufacturing Space exploration Virtual reality
ISSN:	1545-5955, 1558-3783
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