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Collaborative Robotics: Prospects, Challenges and Applications
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Collaborative Robotics: Prospects, Challenges and Applications

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: 25 September 2025 | Viewed by 8669

Special Issue Editors

Dr. Alberto Borboni

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Guest Editor
Department of Mechanical and Industrial Engineering, Università degli Studi di Brescia, 25121 Brescia, Italy
Interests: applied mechanics; robotics; design engineering; physical rehabilitation; engineering; mechatronics
Special Issues, Collections and Topics in MDPI journals
Dr. Giuseppe Carbone

E-Mail Website
Guest Editor
Department of Mechanical, Energy and Management Engineering, Università della Calabria, 87036 Rende, Italy
Interests: robotics; robot design; mechatronics; walking hexapod; design procedure; mechanics of machinery; leg–wheel
Special Issues, Collections and Topics in MDPI journals
Dr. Matteo Claudio Palpacelli

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Guest Editor
Department of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, 60131 Ancona, Italy
Interests: robotics; mechatronics
Prof. Dr. Roberto Pagani

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Guest Editor
Department of Mechanical and Industrial Engineering, Università degli Studi di Brescia, 25121 Brescia, Italy
Interests: collaborative robotics
Antonio Arbore

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Guest Editor Assistant
Independent Researcher, Castegnato, Lombardy, Italy
Interests: exoskeletons; collaborative robots; medical engineering

Special Issue Information

Dear Colleagues,

Cobots, also known as collaborative robots, are designed to collaborate with humans in a shared workspace. There are numerous potential applications for collaborative robotics in industries such as manufacturing, healthcare, and logistics. Utilizing collaborative robots can increase productivity, enhance safety, and reduce labor expenses.

Collaborative robots equipped with artificial intelligence and powerful parallel computing hardware can process complex information from multiple sensors and make autonomous decisions in unpredictably complex environments.

Nevertheless, collaborative robotics presents several challenges. Among these are ensuring safety, integrating with existing systems, and preserving reliability. In addition, workers must be trained to effectively collaborate with robots, and ethical and social implications such as job displacement and privacy concerns, as well as new work organization and the need for new skills, must be addressed.

The potential applications of collaborative robotics are vast despite these challenges. In the manufacturing industry, for instance, collaborative robots can perform dangerous or repetitive tasks while allowing humans to focus on more complex tasks. In the healthcare industry, collaborative robots can aid medical professionals with patient care and physical therapy.

Overall, the application of collaborative robotics is a dynamic and rapidly developing field with numerous growth and innovation opportunities. As technology continues to advance, it is likely that collaborative robotics will play a greater role in a variety of industries.

Dr. Alberto Borboni
Prof. Dr. Giuseppe Carbone
Dr. Matteo Claudio Palpacelli
Prof. Dr. Roberto Pagani
Guest Editors

Antonio Arbore
Guest Editor Assistant

Manuscript Submission Information

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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. Sensors 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 2600 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

  • cobots
  • collaborative robots
  • manufacturing
  • healthcare
  • logistics
  • productivity
  • safety
  • artificial intelligence
  • ethics
  • innovation

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Published Papers (3 papers)

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Research

19 pages, 5446 KiB  
Article
A Novel IMU-Based System for Work-Related Musculoskeletal Disorders Risk Assessment
by Souha Baklouti, Abdelbadia Chaker, Taysir Rezgui, Anis Sahbani, Sami Bennour and Med Amine Laribi
Sensors 2024, 24(11), 3419; https://doi.org/10.3390/s24113419 - 26 May 2024
Cited by 3 | Viewed by 2781
Abstract
This study introduces a novel wearable Inertial Measurement Unit (IMU)-based system for an objective and comprehensive assessment of Work-Related Musculoskeletal Disorders (WMSDs), thus enhancing workplace safety. The system integrates wearable technology with a user-friendly interface, providing magnetometer-free orientation estimation, joint angle measurements, and [...] Read more.
This study introduces a novel wearable Inertial Measurement Unit (IMU)-based system for an objective and comprehensive assessment of Work-Related Musculoskeletal Disorders (WMSDs), thus enhancing workplace safety. The system integrates wearable technology with a user-friendly interface, providing magnetometer-free orientation estimation, joint angle measurements, and WMSDs risk evaluation. Tested in a cable manufacturing facility, the system was evaluated with ten female employees. The evaluation involved work cycle identification, inter-subject comparisons, and benchmarking against standard WMSD risk assessments like RULA, REBA, Strain Index, and Rodgers Muscle Fatigue Analysis. The evaluation demonstrated uniform joint patterns across participants (ICC=0.72±0.23) and revealed a higher occurrence of postures warranting further investigation, which is not easily detected by traditional methods such as RULA. The experimental results showed that the proposed system’s risk assessments closely aligned with the established methods and enabled detailed and targeted risk assessments, pinpointing specific bodily areas for immediate ergonomic interventions. This approach not only enhances the detection of ergonomic risks but also supports the development of personalized intervention strategies, addressing common workplace issues such as tendinitis, low back pain, and carpal tunnel syndrome. The outcomes highlight the system’s sensitivity and specificity in identifying ergonomic hazards. Future efforts should focus on broader validation and exploring the relative influence of various WMSDs risk factors to refine risk assessment and intervention strategies for improved applicability in occupational health. Full article
(This article belongs to the Special Issue Collaborative Robotics: Prospects, Challenges and Applications)
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12 pages, 20111 KiB  
Article
A Robot-Assisted Framework for Rehabilitation Practices: Implementation and Experimental Results
by Giorgia Chiriatti, Luca Carbonari, Maria Gabriella Ceravolo, Elisa Andrenelli, Marzia Millevolte and Giacomo Palmieri
Sensors 2023, 23(17), 7652; https://doi.org/10.3390/s23177652 - 4 Sep 2023
Cited by 3 | Viewed by 1760
Abstract
One of the most interesting characteristics of collaborative robots is their ability to be used in close cooperation scenarios. In industry, this facilitates the implementation of human-in-loop workflows. However, this feature can also be exploited in different fields, such as healthcare. In this [...] Read more.
One of the most interesting characteristics of collaborative robots is their ability to be used in close cooperation scenarios. In industry, this facilitates the implementation of human-in-loop workflows. However, this feature can also be exploited in different fields, such as healthcare. In this paper, a rehabilitation framework for the upper limbs of neurological patients is presented, consisting of a collaborative robot that helps users perform three-dimensional trajectories. Such a practice is aimed at improving the coordination of patients by guiding their motions in a preferred direction. We present the mechatronic setup, along with a preliminary experimental set of results from 19 volunteers (patients and control subjects) who provided positive feedback on the training experience (52% of the subjects would return and 44% enjoyed performing the exercise). Patients were able to execute the exercise, with a maximum deviation from the trajectory of 16 mm. The muscular effort required was limited, with average maximum forces recorded at around 50 N. Full article
(This article belongs to the Special Issue Collaborative Robotics: Prospects, Challenges and Applications)
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27 pages, 5993 KiB  
Article
Role of Reference Frames for a Safe Human–Robot Interaction
by Alberto Borboni, Roberto Pagani, Samuele Sandrini, Giuseppe Carbone and Nicola Pellegrini
Sensors 2023, 23(12), 5762; https://doi.org/10.3390/s23125762 - 20 Jun 2023
Cited by 4 | Viewed by 2304
Abstract
Safety plays a key role in human–robot interactions in collaborative robot (cobot) applications. This paper provides a general procedure to guarantee safe workstations allowing human operations, robot contributions, the dynamical environment, and time-variant objects in a set of collaborative robotic tasks. The proposed [...] Read more.
Safety plays a key role in human–robot interactions in collaborative robot (cobot) applications. This paper provides a general procedure to guarantee safe workstations allowing human operations, robot contributions, the dynamical environment, and time-variant objects in a set of collaborative robotic tasks. The proposed methodology focuses on the contribution and the mapping of reference frames. Multiple reference frame representation agents are defined at the same time by considering egocentric, allocentric, and route-centric perspectives. The agents are processed to provide a minimal and effective assessment of the ongoing human–robot interactions. The proposed formulation is based on the generalization and proper synthesis of multiple cooperating reference frame agents at the same time. Accordingly, it is possible to achieve a real-time assessment of the safety-related implications through the implementation and fast calculation of proper safety-related quantitative indices. This allows us to define and promptly regulate the controlling parameters of the involved cobot without velocity limitations that are recognized as the main disadvantage. A set of experiments has been realized and investigated to demonstrate the feasibility and effectiveness of the research by using a seven-DOF anthropomorphic arm in combination with a psychometric test. The acquired results agree with the current literature in terms of the kinematic, position, and velocity aspects; use measurement methods based on tests provided to the operator; and introduce novel features of work cell arranging, including the use of virtual instrumentation. Finally, the associated analytical–topological treatments have enabled the development of a safe and comfortable measure to the human–robot relation with satisfactory experimental results compared to previous research. Nevertheless, the robot posture, human perception, and learning technologies would have to apply research from multidisciplinary fields such as psychology, gesture, communication, and social sciences in order to be prepared for positioning in real-world applications that offer new challenges for cobot applications. Full article
(This article belongs to the Special Issue Collaborative Robotics: Prospects, Challenges and Applications)
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