Mutual-cognition for proactive human–robot collaboration: A mixed reality-enabled visual reasoning-based method

Shufei Li, Yingchao You, Pai Zheng, Xi Vincent Wang, Lihui Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

4 Citations (Scopus)

Abstract

Human-Robot Collaboration (HRC) is key to achieving the flexible automation required by the mass personalization trend, especially towards human-centric intelligent manufacturing. Nevertheless, existing HRC systems suffer from poor task understanding and poor ergonomic satisfaction, which impede empathetic teamwork skills in task execution. To overcome the bottleneck, a Mixed Reality (MR) and visual reasoning-based method is proposed in this research, providing mutual-cognitive task assignment for human and robotic agents’ operations. Firstly, an MR-enabled mutual-cognitive HRC architecture is proposed, with the characteristic of monitoring Digital Twins states, reasoning co-working strategies, and providing cognitive services. Secondly, a visual reasoning approach is introduced, which learns scene interpretation from the visual perception of each agent’s actions and environmental changes to make task planning strategies satisfying human–robot operation needs. Lastly, a safe, ergonomic, and proactive robot motion planning algorithm is proposed to let a robot execute generated co-working strategies, while a human operator is supported with intuitive task operation guidance in the MR environment, achieving empathetic collaboration. Through a demonstration of a disassembly task of aging Electric Vehicle Batteries, the experimental result facilitates cognitive intelligence in Proactive HRC for flexible automation.

Original languageEnglish
Pages (from-to)1099-1111
Number of pages13
JournalIISE Transactions
Volume56
Issue number10
DOIs
Publication statusPublished - 11 Mar 2024

Keywords

  • ergonomic robot control
  • human-centric manufacturing
  • Human-robot collaboration
  • mixed reality
  • visual reasoning

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

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