Sökning: onr:"swepub:oai:DiVA.org:kth-345692" >
Unleashing mixed-re...
Unleashing mixed-reality capability in Deep Reinforcement Learning-based robot motion generation towards safe human–robot collaboration
-
- Li, Chengxi (författare)
- Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China; Laboratory for Artificial Intelligence in Design, Hong Kong Science Park, Hong Kong Special Administrative Region, China; Department of Aerospace and Mechanical Engineering, Viterbi School of Engineering, University of Southern California, L.A., United States
-
- Zheng, Pai (författare)
- Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China; Laboratory for Artificial Intelligence in Design, Hong Kong Science Park, Hong Kong Special Administrative Region, China
-
- Zhou, Peng (författare)
- Department of Computer Science, The University of Hong Kong, Hong Kong Special Administrative Region, China
-
visa fler...
-
- Yin, Yue (författare)
- Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China
-
- Lee, Carman K.M. (författare)
- Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China; Laboratory for Artificial Intelligence in Design, Hong Kong Science Park, Hong Kong Special Administrative Region, China
-
- Wang, Lihui (författare)
- KTH,Produktionsutveckling
-
visa färre...
-
Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China; Laboratory for Artificial Intelligence in Design, Hong Kong Science Park, Hong Kong Special Administrative Region, China; Department of Aerospace and Mechanical Engineering, Viterbi School of Engineering, University of Southern California, LA., United States Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong Special Administrative Region, China; Laboratory for Artificial Intelligence in Design, Hong Kong Science Park, Hong Kong Special Administrative Region, China (creator_code:org_t)
- Elsevier B.V. 2024
- 2024
- Engelska.
-
Ingår i: Journal of manufacturing systems. - : Elsevier B.V.. - 0278-6125 .- 1878-6642. ; 74, s. 411-421
- Relaterad länk:
-
https://urn.kb.se/re...
-
visa fler...
-
https://doi.org/10.1...
-
visa färre...
Abstract
Ämnesord
Stäng
- The integration of human–robot collaboration yields substantial benefits, particularly in terms of enhancing flexibility and efficiency within a range of mass-personalized manufacturing tasks, for example, small-batch customized product inspection and assembly/disassembly. Meanwhile, as human–robot collaboration lands broader in manufacturing, the unstructured scene and operator uncertainties are increasingly involved and considered. Consequently, it becomes imperative for robots to execute in a safe and adaptive manner rather than solely relying on pre-programmed instructions. To tackle it, a systematic solution for safe robot motion generation in human–robot collaborative activities is proposed, leveraging mixed-reality technologies and Deep Reinforcement Learning. This solution covers the entire process of collaboration starting with an intuitive interface that facilitates bare-hand task command transmission and scene coordinate transformation before the collaboration begins. In particular, mixed-reality devices are employed as effective tools for representing the state of humans, robots, and scenes. This enables the learning of an end-to-end Deep Reinforcement Learning policy that addresses both the uncertainties in robot perception and decision-making in an integrated manner. The proposed solution also implements policy simulation-to-reality deployment, along with motion preview and collision detection mechanisms, to ensure safe robot motion execution. It is hoped that this work could inspire further research in human–robot collaboration to unleash and exploit the powerful capabilities of mixed reality.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Robotteknik och automation (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Robotics (hsv//eng)
Nyckelord
- Deep Reinforcement Learning
- Human–robot collaboration
- Manufacturing safety
- Mixed reality
- Smart manufacturing
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
Hitta via bibliotek
Till lärosätets databas