An Active Assistant Robotic System Based on High-Speed Vision and Haptic Feedback for Human-Robot Collaboration

Huang, Shouren; Ishikawa, Masatoshi; Yamakawa, Yuji

doi:10.1109/iecon.2018.8592810

Cited by 9 publications

(1 citation statement)

References 11 publications

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“…Lightweight collaborative robots, such as those that have come to the market for assembly applications in recent years [110], allow human haptic guidance [82,35], in particular, to enable intuitive and efficient teach-in of individual poses or playback of movement profiles. Due to the low load-bearing capacity, they are not intended to relieve the physical burden on humans in the context of collaborative task execution [219].…”

Section:  Motion Control: the Robot Movements Occur Simultaneouslymentioning

confidence: 99%

Symbiotic human-robot collaborative assembly

et al. 2019

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In human-robot collaborative assembly, robots are often required to dynamically change their pre-planned tasks to collaborate with human operators in a shared workspace. However, the robots used today are controlled by pre-generated rigid codes that cannot support effective human-robot collaboration. In response to this need, multi-modal yet symbiotic communication and control methods have been a focus in recent years. These methods include voice processing, gesture recognition, haptic interaction, and brainwave perception. Deep learning is used for classification, recognition and context awareness identification. Within this context, this keynote provides an overview of symbiotic human-robot collaborative assembly and highlights future research directions.

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