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Applied Sciences
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Human–Robot Collaboration and Its Applications
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Human–Robot Collaboration and Its Applications

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".

Deadline for manuscript submissions: 20 October 2025 | Viewed by 1348

Special Issue Editors

Prof. Dr. Angel Valera

E-Mail Website
Guest Editor
Instituto Universitario de Automática e Informática Industrial (Instituto ai2), Universitat Politècnica de València, 46022 Valencia, Spain
Interests: systems engineering; robots; human–robot collaboration; Industry 4.0; position and force robot control; artificial intelligence; advanced robotics; industrial applications; safety systems
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Marina Valles

E-Mail Website
Guest Editor
Departamento de Ingeniería de Sistemas y Automática, Instituto de Automática e Informática Industrial, Universitat Politècnica de València, 46022 Valencia, Spain
Interests: human–robot collaboration; Industry 4.0; position and force robot control; artificial intelligence; advanced robotics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The automation of manufacturing is moving toward mass production and customization through human–robot collaboration (HRC), a new trend in the field of industrial and service robotics as part of the Industry 4.0 strategy. The main objective of this innovative strategy is to create an environment of safe collaboration between humans and robots.

Robots help humans with non-ergonomic, repetitive, uncomfortable or even dangerous operations with high precision and repeatability. Humans can quickly identify hazards and apply them in decision making thanks to their intelligence and flexibility. The integration of human and robot characteristics can build an efficient collaborative system to bring an enormous improvement in flexibility.

This Special Issue aims to publish high-quality papers and disseminate the latest research achievements, findings, and ideas in the field of human–robot collaboration. The recommended topics include, but are not limited to, the following:

  • Human–robot collaboration and interaction for industrial applications;
  • Collaborative and cooperative robots;
  • Digital manufacturing systems and applications areas.

Prof. Dr. Angel Valera
Prof. Dr. Marina Valles
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • human–robot collaboration
  • human–robot interaction
  • Industry 4.0
  • robot control
  • artificial intelligence
  • advanced robotics
  • industrial robotics

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Published Papers (1 paper)

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Research

20 pages, 36005 KiB  
Article
A Carpometacarpal Thumb Tracking Device for Telemanipulation of a Robotic Thumb: Development, Prototyping, and Evaluation
by Abdul Hafiz Abdul Rahaman and Panos S. Shiakolas
Appl. Sci. 2025, 15(3), 1301; https://doi.org/10.3390/app15031301 - 27 Jan 2025
Viewed by 713
Abstract
Hand−tracking systems are widely employed for telemanipulating grippers with high degrees of freedom (DOFs) such as an anthropomorphic robotic hand (ARH). However, tracking human thumb motion is challenging due to the complex motion of the carpometacarpal (CMC) joint. Existing hand−tracking systems can track [...] Read more.
Hand−tracking systems are widely employed for telemanipulating grippers with high degrees of freedom (DOFs) such as an anthropomorphic robotic hand (ARH). However, tracking human thumb motion is challenging due to the complex motion of the carpometacarpal (CMC) joint. Existing hand−tracking systems can track the motion of simple joints with one DOF, but most fail to track the motion of the CMC joint, or to do so, there is a need for expensive and intricately set up hardware systems. This research introduces and realizes an affordable and personalizable tracking device to capture the CMC joint Flexion/Extension and Abduction/Adduction motions. Tracked human thumb motion is mapped to a robot thumb in a hybrid approach: the proposed algorithm maps the CMC joint motion to the first two joints of the robot thumb, while joint mapping is established between the metacarpophalangeal and interphalangeal joints to the last two joints. When the tracking device is paired with a flex glove outfitted with bend sensors, the developed system provides the means to telemanipulate an ARH with a four-DOF thumb and one-DOF underactuated digits. A three-stage framework is proposed to telemanipulate the fully actuated robot thumb. The tracking device and framework were evaluated through a device operation and personalization test, as well as a framework verification test. Two volunteers successfully personalized, calibrated, and tested the device using the proposed mapping algorithm. One volunteer further evaluated the framework by performing hand poses and grasps, demonstrating effective control of the robot thumb for precision and power grasps in coordination with the other digits. The successful results support expanding the system and further evaluating it as a research platform for studying human–robot interaction in grasping tasks or in manufacturing, assistive, or medical domains. Full article
(This article belongs to the Special Issue Human–Robot Collaboration and Its Applications)
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