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Robotics
Special Issues
Human–Robot Collaboration
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Human–Robot Collaboration

A special issue of Robotics (ISSN 2218-6581).

Deadline for manuscript submissions: closed (31 January 2021) | Viewed by 38768

Special Issue Editors

Prof. Dr. Giacomo Palmieri

E-Mail Website
Guest Editor
Department of Industrial Engineering & Mathematical Sciences, Polytechnic University of Marche, 60131 Ancona, Italy
Interests: collaborative robotics; mechatronics and biomechanics; kinematic and dynamic analysis and synthesis of mechanical and biomechanical systems
Prof. Dr. Aman Behal

E-Mail Website
Guest Editor
Department of Electrical and Computer Engineering and the NanoScience Technology Center, University of Central Florida, Orlando, FL 32816, USA
Interests: assistive robotics; human–robot interaction; nonlinear control theory and applications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Collaborative robotics has now fully entered the industrial technological panorama, along with all the enabling technologies of the current industrial transformation, also known as Industry 4.0. Such transformation is possible thanks to the synergy of different disciplines, such as mechanics, control, and artificial intelligence, giving full implementation to the novel concept of mechatronics. Research and experimentation play a central role so that collaborative robotics can offer advantages both for the competitiveness of companies and for the quality of the operators' work. However, many areas of research have not been fully explored and represent a challenge for the scientific community; novel insights are emerging in the field of safety techniques, innovative collaboration methods, novel fields of application, integration of advanced sensor systems, etc. Even the ethics and socio-economic implications of this field are matters of deep interest.

This Special Issue will collect novel works in the area of human–robot collaboration (HRC), with contributions from different disciplines and backgrounds, including mechanics, robotics, control, mechatronics, artificial intelligence, ergonomics, and others. The aim is to outline the state of the art in terms of design, applications, and methods and to identify challenges for future research in this field. For these reasons, review papers will also be considered favorably.

Topics of interest include, but are not limited to, the following:

  • Collaborative robots and mobile collaborative robots: design and applications;
  • Control strategies and artificial intelligence for HRC;
  • Novel fields for HRC: advanced industrial applications, motor rehabilitation, educational robotics, etc.;
  • Ergonomics in HRC;
  • Collaborative devices;
  • Standardization and risk assessment;
  • Contact estimation and collision avoidance;
  • Human factors in collaborative robotics.

Prof. Dr. Giacomo Palmieri
Prof. Dr. Aman Behal
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. Robotics is an international peer-reviewed open access monthly 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 1800 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

  • collaborative robotics
  • human–robot collaboration
  • human–robot interfaces
  • safety in collaborative robotics
  • control strategies for HRC
  • artificial intelligence for HRC
  • mobile collaborative robotics
  • rehabilitation by collaborative robotics
  • ergonomics in HRC

Published Papers (6 papers)

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Research

20 pages, 2325 KiB  
Article
Validating Safety in Human–Robot Collaboration: Standards and New Perspectives
by Marcello Valori, Adriano Scibilia, Irene Fassi, José Saenz, Roland Behrens, Sebastian Herbster, Catherine Bidard, Eric Lucet, Alice Magisson, Leendert Schaake, Jule Bessler, Gerdienke B. Prange-Lasonder, Morten Kühnrich, Aske B. Lassen and Kurt Nielsen
Robotics 2021, 10(2), 65; https://doi.org/10.3390/robotics10020065 - 29 Apr 2021
Cited by 44 | Viewed by 9399
Abstract
Human–robot collaboration is currently one of the frontiers of industrial robot implementation. In parallel, the use of robots and robotic devices is increasing in several fields, substituting humans in “4D”—dull, dirty, dangerous, and delicate—tasks, and such a trend is boosted by the recent [...] Read more.
Human–robot collaboration is currently one of the frontiers of industrial robot implementation. In parallel, the use of robots and robotic devices is increasing in several fields, substituting humans in “4D”—dull, dirty, dangerous, and delicate—tasks, and such a trend is boosted by the recent need for social distancing. New challenges in safety assessment and verification arise, due to both the closer and closer human–robot interaction, common for the different application domains, and the broadening of user audience, which is now very diverse. The present paper discusses a cross-domain approach towards the definition of step-by-step validation procedures for collaborative robotic applications. To outline the context, the standardization framework is analyzed, especially from the perspective of safety testing and assessment. Afterwards, some testing procedures based on safety skills, developed within the framework of the European project COVR, are discussed and exemplary presented. Full article
(This article belongs to the Special Issue Human–Robot Collaboration)
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23 pages, 3942 KiB  
Article
FES Cycling and Closed-Loop Feedback Control for Rehabilitative Human–Robot Interaction
by Christian Cousin, Victor Duenas and Warren Dixon
Robotics 2021, 10(2), 61; https://doi.org/10.3390/robotics10020061 - 22 Apr 2021
Cited by 9 | Viewed by 5119
Abstract
For individuals with movement impairments due to neurological injuries, rehabilitative therapies such as functional electrical stimulation (FES) and rehabilitation robots hold vast potential to improve their mobility and activities of daily living. Combining FES with rehabilitation robots results in intimately coordinated human–robot interaction. [...] Read more.
For individuals with movement impairments due to neurological injuries, rehabilitative therapies such as functional electrical stimulation (FES) and rehabilitation robots hold vast potential to improve their mobility and activities of daily living. Combining FES with rehabilitation robots results in intimately coordinated human–robot interaction. An example of such interaction is FES cycling, where motorized assistance can provide high-intensity and repetitive practice of coordinated limb motion, resulting in physiological and functional benefits. In this paper, the development of multiple FES cycling testbeds and safeguards is described, along with the switched nonlinear dynamics of the cycle–rider system. Closed-loop FES cycling control designs are described for cadence and torque tracking. For each tracking objective, the authors’ past work on robust and adaptive controllers used to compute muscle stimulation and motor current inputs is presented and discussed. Experimental results involving both able-bodied individuals and participants with neurological injuries are provided for each combination of controller and tracking objective. Trade-offs for the control algorithms are discussed based on the requirements for implementation, desired rehabilitation outcomes and resulting rider performance. Lastly, future works and the applicability of the developed methods to additional technologies including teleoperated robotics are outlined. Full article
(This article belongs to the Special Issue Human–Robot Collaboration)
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14 pages, 6284 KiB  
Communication
Human–Robot Interaction through Eye Tracking for Artistic Drawing
by Lorenzo Scalera, Stefano Seriani, Paolo Gallina, Mattia Lentini and Alessandro Gasparetto
Robotics 2021, 10(2), 54; https://doi.org/10.3390/robotics10020054 - 26 Mar 2021
Cited by 32 | Viewed by 7074
Abstract
In this paper, authors present a novel architecture for controlling an industrial robot via an eye tracking interface for artistic purposes. Humans and robots interact thanks to an acquisition system based on an eye tracker device that allows the user to control the [...] Read more.
In this paper, authors present a novel architecture for controlling an industrial robot via an eye tracking interface for artistic purposes. Humans and robots interact thanks to an acquisition system based on an eye tracker device that allows the user to control the motion of a robotic manipulator with his gaze. The feasibility of the robotic system is evaluated with experimental tests in which the robot is teleoperated to draw artistic images. The tool can be used by artists to investigate novel forms of art and by amputees or people with movement disorders or muscular paralysis, as an assistive technology for artistic drawing and painting, since, in these cases, eye motion is usually preserved. Full article
(This article belongs to the Special Issue Human–Robot Collaboration)
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23 pages, 1183 KiB  
Article
Explanations from a Robotic Partner Build Trust on the Robot’s Decisions for Collaborative Human-Humanoid Interaction
by Misbah Javaid and Vladimir Estivill-Castro
Robotics 2021, 10(1), 51; https://doi.org/10.3390/robotics10010051 - 23 Mar 2021
Cited by 6 | Viewed by 4800
Abstract
Typically, humans interact with a humanoid robot with apprehension. This lack of trust can seriously affect the effectiveness of a team of robots and humans. We can create effective interactions that generate trust by augmenting robots with an explanation capability. The explanations provide [...] Read more.
Typically, humans interact with a humanoid robot with apprehension. This lack of trust can seriously affect the effectiveness of a team of robots and humans. We can create effective interactions that generate trust by augmenting robots with an explanation capability. The explanations provide justification and transparency to the robot’s decisions. To demonstrate such effective interaction, we tested this with an interactive, game-playing environment with partial information that requires team collaboration, using a game called Spanish Domino. We partner a robot with a human to form a pair, and this team opposes a team of two humans. We performed a user study with sixty-three human participants in different settings, investigating the effect of the robot’s explanations on the humans’ trust and perception of the robot’s behaviour. Our explanation-generation mechanism produces natural-language sentences that translate the decision taken by the robot into human-understandable terms. We video-recorded all interactions to analyse factors such as the participants’ relational behaviours with the robot, and we also used questionnaires to measure the participants’ explicit trust in the robot. Overall, our main results demonstrate that explanations enhanced the participants’ understandability of the robot’s decisions, because we observed a significant increase in the participants’ level of trust in their robotic partner. These results suggest that explanations, stating the reason(s) for a decision, combined with the transparency of the decision-making process, facilitate collaborative human–humanoid interactions. Full article
(This article belongs to the Special Issue Human–Robot Collaboration)
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18 pages, 2917 KiB  
Article
Cobot User Frame Calibration: Evaluation and Comparison between Positioning Repeatability Performances Achieved by Traditional and Vision-Based Methods
by Roberto Pagani, Cristina Nuzzi, Marco Ghidelli, Alberto Borboni, Matteo Lancini and Giovanni Legnani
Robotics 2021, 10(1), 45; https://doi.org/10.3390/robotics10010045 - 8 Mar 2021
Cited by 14 | Viewed by 5253
Abstract
Since cobots are designed to be flexible, they are frequently repositioned to change the production line according to the needs; hence, their working area (user frame) needs to be often calibrated. Therefore, it is important to adopt a fast and intuitive user frame [...] Read more.
Since cobots are designed to be flexible, they are frequently repositioned to change the production line according to the needs; hence, their working area (user frame) needs to be often calibrated. Therefore, it is important to adopt a fast and intuitive user frame calibration method that allows even non-expert users to perform the procedure effectively, reducing the possible mistakes that may arise in such contexts. The aim of this work was to quantitatively assess the performance of different user frame calibration procedures in terms of accuracy, complexity, and calibration time, to allow a reliable choice of which calibration method to adopt and the number of calibration points to use, given the requirements of the specific application. This has been done by first analyzing the performances of a Rethink Robotics Sawyer robot built-in user frame calibration method (Robot Positioning System, RPS) based on the analysis of a fiducial marker distortion obtained from the image acquired by the wrist camera. This resulted in a quantitative analysis of the limitations of this approach that only computes local calibration planes, highlighting the reduction of performances observed. Hence, the analysis focused on the comparison between two traditional calibration methods involving rigid markers to determine the best number of calibration points to adopt to achieve good repeatability performances. The analysis shows that, among the three methods, the RPS one resulted in very poor repeatability performances (1.42 mm), while the three and five points calibration methods achieve lower values (0.33 mm and 0.12 mm, respectively) which are closer to the reference repeatability (0.08 mm). Moreover, comparing the overall calibration times achieved by the three methods, it is shown that, incrementing the number of calibration points to more than five, it is not suggested since it could lead to a plateau in the performances, while increasing the overall calibration time. Full article
(This article belongs to the Special Issue Human–Robot Collaboration)
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10 pages, 13790 KiB  
Communication
Determining Robotic Assistance for Inclusive Workplaces for People with Disabilities
by Elodie Hüsing, Carlo Weidemann, Michael Lorenz, Burkhard Corves and Mathias Hüsing
Robotics 2021, 10(1), 44; https://doi.org/10.3390/robotics10010044 - 5 Mar 2021
Cited by 9 | Viewed by 4336
Abstract
Human–robot collaboration (HRC) provides the opportunity to enhance the physical abilities of severely and multiply disabled people thus allowing them to work in industrial workplaces on the primary labour market. In order to assist this target group optimally, the collaborative robot has to [...] Read more.
Human–robot collaboration (HRC) provides the opportunity to enhance the physical abilities of severely and multiply disabled people thus allowing them to work in industrial workplaces on the primary labour market. In order to assist this target group optimally, the collaborative robot has to support them based on their individual capabilities. Therefore, the knowledge about the amount of required assistance is a central aspect for the design and programming of HRC workplaces. The paper introduces a new method that bases the task allocation on the individual capabilities of a person. The method obtains human capabilities on the one hand and the process requirements on the other. In the following step, these two profiles are compared and the workload of the human is acquired. This determines the amount of support or assistance, which should be provided by a robot capable of HRC. In the end, the profile comparison of an anonymized participant and the concept of the human–robot workplace is presented. Full article
(This article belongs to the Special Issue Human–Robot Collaboration)
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