Simpler rather than Challenging: Design of Non-Dyadic Human-Robot Collaboration to Mediate Human-Human Concurrent Tasks

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Abstract

Human-robot interaction (HRI) is progressively addressing multiparty scenarios, where a robot interacts with more than one human user at the same time. Conversely, research in this area is still at an early stage for human-robot collaboration (HRC). The intervention of a robot in human collaboration could be helpful to handle mutual disturbances of workers operating at the same time on the same target object. Therefore, this work outlines design methodologies of non-dyadic human-robot collaborations to address concurrent human-human tasks in manufacturing applications. After this, preliminary results regarding a robotic agent’s high-level understanding of such scenarios realised through a variational autoencoder trained by means of transfer learning are shown.
Original languageEnglish
Title of host publication22nd International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2023), London
PublisherAssociation for Computing Machinery
DOIs
Publication statusPublished - 30 May 2023

Keywords

  • Non-Dyadic Human-Robot Collaboration
  • Multi-Party Human-Robot Collaboration
  • Concurrent Tasks
  • Multi-User Activity Recognition
  • Deep Learning
  • Variational Autoencoder
  • Transfer Learning

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