Intelligent Human–Robot Interaction: 3rd Edition

A special issue of Biomimetics (ISSN 2313-7673). This special issue belongs to the section "Locomotion and Bioinspired Robotics".

Deadline for manuscript submissions: 31 March 2025 | Viewed by 789

Special Issue Editors


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Guest Editor
School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China
Interests: intelligent remanufacturing technology; robotics and automation; human-machine collaboration; optical fiber sensing and intelligent sensing technology; mechanical equipment condition monitoring and fault diagnosis
Special Issues, Collections and Topics in MDPI journals
School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan 430070, China
Interests: fiber optic sensing; robot force/position hybrid control; special robot
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Human–robot interaction (HRI) is a multi-disciplinary field that encompasses artificial intelligence, robotics, human–computer interaction, machine vision, natural language understanding, and social science. With the rapid development of AI and robotics, intelligent HRI has become an increasingly attractive issue in the field of robotics.

Intelligent HRI involves many challenges in science and technology, particularly in human-centered aspects. These include human expectations, attitudes towards, and perceptions of robots; the safety, acceptability, and comfort with robotic behaviors; and the closeness of robots to humans. On the other hand, it is desired for robots to understand the attention, intention, and even emotion of humans and make prompt corresponding responses with the support of AI. Achieving excellent intelligent HRI requires R&D in this multi- and cross-disciplinary field, with efforts expected in all relevant aspects including actuation, sensing, perception, control, recognition, planning, learning, AI algorithms, intelligent IO, integrated systems, and so on.

The aim of this Special Issue is to reveal new concepts, ideas, findings, and the latest achievements in both theoretical research and technical development in intelligent HRI. We invite scientists and engineers from robotics, AI, computer science, and other relevant disciplines to present the latest results of their research and development in the field of intelligent HRI. The topics of interest include, but are not limited to, the following:

  • Intelligent sensors and systems;
  • Bio-inspired sensing and learning;
  • Multi-modal perception and recognition;
  • Social robotics;
  • Autonomous behaviors of robots;
  • AI algorithms in robotics;
  • Collaboration between humans and robots;
  • Advances and future challenges of HRI.

Prof. Dr. Jun Huang
Dr. Ruiya Li
Guest Editors

Manuscript Submission Information

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Keywords

  • intelligent sensors and systems
  • bio-inspired sensing and learning
  • multi-modal perception and recognition
  • social robotics
  • autonomous behaviors of robots
  • AI algorithms in robotics
  • collaboration between humans and robots
  • advances and future challenges of HRI

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Published Papers (1 paper)

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29 pages, 5444 KiB  
Article
Task Allocation and Sequence Planning for Human–Robot Collaborative Disassembly of End-of-Life Products Using the Bees Algorithm
by Jun Huang, Sheng Yin, Muyao Tan, Quan Liu, Ruiya Li and Duc Pham
Biomimetics 2024, 9(11), 688; https://doi.org/10.3390/biomimetics9110688 - 11 Nov 2024
Viewed by 649
Abstract
Remanufacturing, which benefits the environment and saves resources, is attracting increasing attention. Disassembly is arguably the most critical step in the remanufacturing of end-of-life (EoL) products. Human–robot collaborative disassembly as a flexible semi-automated approach can increase productivity and relieve people of tedious, laborious, [...] Read more.
Remanufacturing, which benefits the environment and saves resources, is attracting increasing attention. Disassembly is arguably the most critical step in the remanufacturing of end-of-life (EoL) products. Human–robot collaborative disassembly as a flexible semi-automated approach can increase productivity and relieve people of tedious, laborious, and sometimes hazardous jobs. Task allocation in human–robot collaborative disassembly involves methodically assigning disassembly tasks to human operators or robots. However, the schemes for task allocation in recent studies have not been sufficiently refined and the issue of component placement after disassembly has not been fully addressed in recent studies. This paper presents a method of task allocation and sequence planning for human–robot collaborative disassembly of EoL products. The adopted criteria for human–robot disassembly task allocation are introduced. The disassembly of each component includes dismantling and placing. The performance of a disassembly plan is evaluated according to the time, cost, and utility value. A discrete Bees Algorithm using genetic operators is employed to optimise the generated human–robot collaborative disassembly solutions. The proposed task allocation and sequence planning method is validated in two case studies involving an electric motor and a power battery from an EoL vehicle. The results demonstrate the feasibility of the proposed method for planning and optimising human–robot collaborative disassembly solutions. Full article
(This article belongs to the Special Issue Intelligent Human–Robot Interaction: 3rd Edition)
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