Assessment, Validation and Improvement of Safety and Ergonomics in Human-Robot Interaction

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Automation and Control Systems".

Deadline for manuscript submissions: 28 February 2025 | Viewed by 12230

Special Issue Editors


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Guest Editor
National Research Council of Italy (CNR), Institute of Intellingent Industrial Systems and Technologies for Advanced Manufacturing, Via P. Lembo 38/F, Bari, Italy
Interests: human–robot collaboration; robot safety; robot assembly; robotics

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Guest Editor
Faculty of Science and Technology, Free University of Bozen-Bolzano, 39100 Bolzano, Italy
Interests: human–robot collaboration; safety; ergonomics; collaborative assembly systems
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Fraunhofer Institute for Factory Operation and Automation IFF, 39106 Magdeburg, Germany
Interests: human–robot collaboration; safety; industrial robots; assistive robots

Special Issue Information

Dear Colleagues,

The increasing advancements in robotic technologies enable new applications and new fields of interest. At the same time, the role of robotic devices is evolving in traditional application fields, such as industry. In the robotization era, human–robot interactions (HRIs) push the limit toward optimal and synergistic paradigms for the execution of tasks.

As a consequence of the closer human–robot interactions, the current challenges in robotic implementation go beyond the technological issues, including safety and ergonomics as fundamental boundaries. Safety-related considerations apply to the whole development, implementation and lifecycle of applications, requiring specific approaches for assessment and validation, control strategies, and other equipment. Furthermore, ergonomics (both physical and cognitive) is fundamental for implementing safe, fluent and efficient collaborative applications. These aspects are even more significant in the context of the Industry 5.0 worker-centric paradigm, where a worker’s well-being plays a large role.

This Special Issue focuses on the research efforts dealing with the latest safety and ergonomic challenges arising in the assessment, validation and improvement of collaborative robotic applications, while also considering integrated design methodologies, ranging from industry and smart factories to novel application fields. Suitable topics include, but are not limited to:

  • Design and application of human-centered applications;
  • Novel approaches for risk assessment and mitigation;
  • Safety-oriented application design;
  • Human–robot contact and collision: modeling and validation;
  • Improvement of a system’s physical and cognitive ergonomics;
  • Advanced architectures and equipment for safe and ergonomic interactions;
  • Validation approaches and techniques.

Dr. Marcello Valori
Dr. Luca Gualtieri
Dr. José Saenz
Dr. Irene Fassi
Guest Editors

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Keywords

  • human–robot interaction
  • human–robot collaboration
  • safety
  • ergonomics
  • risk assessment
  • safety validation
  • collaborative robots

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Published Papers (6 papers)

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Research

16 pages, 1994 KiB  
Article
Human Reliability Assessment of Space Teleoperation Based on ISM-BN
by Hongrui Zhang, Shanguang Chen and Rongji Dai
Machines 2024, 12(8), 524; https://doi.org/10.3390/machines12080524 - 31 Jul 2024
Viewed by 496
Abstract
Space teleoperation systems, as complex giant systems, feature performance-influencing factors that are interrelated. Accurately describing the dependence between these factors is crucial for constructing a human factor reliability assessment (HRA) model. Moreover, data scarcity has consistently been a challenge in space HRA. There [...] Read more.
Space teleoperation systems, as complex giant systems, feature performance-influencing factors that are interrelated. Accurately describing the dependence between these factors is crucial for constructing a human factor reliability assessment (HRA) model. Moreover, data scarcity has consistently been a challenge in space HRA. There are primarily two types of data in this domain: expert judgment data and empirical data (simulation data, actual reports), each with complementary effects. The expert judgment data, although subjective, are readily accessible, while empirical data provide robust objectivity but are difficult to obtain. Addressing these challenges, this paper constructs an HRA model for space teleoperation that combines Interpretive Structural Modeling (ISM) with a two-stage Bayesian update method. This model reflects the dependencies between factors and accommodates multisource data (expert judgment and experimental data). With more empirical data, the model can be continuously updated and refined to yield increasingly accurate evaluations of human error probability (HEP). The validity of the model was verified through the analysis of 52 space incidents using the N-K model. The study provides a methodological foundation for HRA in other space missions. Full article
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16 pages, 7680 KiB  
Article
Physical Ergonomics Monitoring in Human–Robot Collaboration: A Standard-Based Approach for Hand-Guiding Applications
by Eugenio Monari, Giulia Avallone, Marcello Valori, Lorenzo Agostini, Yi Chen, Emanuele Palazzi and Rocco Vertechy
Machines 2024, 12(4), 231; https://doi.org/10.3390/machines12040231 - 30 Mar 2024
Cited by 1 | Viewed by 2490
Abstract
Human–robot collaboration stands as one of the research frontiers in industrial applications due to the possibility for human operators to be supported by robots in carrying out their tasks in a shared workspace. However, advances in this field can be slowed down by [...] Read more.
Human–robot collaboration stands as one of the research frontiers in industrial applications due to the possibility for human operators to be supported by robots in carrying out their tasks in a shared workspace. However, advances in this field can be slowed down by the lack of standards regarding the safety and ergonomics of such applications. This article aims at reducing this gap by presenting an adaptation of the standard ISO 11228-3 for the ergonomic evaluation of hand-guiding applications through the OCRA index. This innovative methodology is innovatively applied to a drilling application in which a human operator hand-guides a collaborative robotic system consisting of a Franka Emika Panda robot, a force/torque sensor and an IMU suit to track the motion of the operator’s body. The SaRAH app, a MATLAB 2020a-based software tool developed on purpose, implements the ergonomic assessment procedure, allowing the proper redesign of the working shift (offline mode) or providing the worker suggestions to improve his/her behavior (online mode) so as to reduce the ergonomic risk. Full article
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16 pages, 9482 KiB  
Article
Action Recognition for Human–Robot Teaming: Exploring Mutual Performance Monitoring Possibilities
by Shakra Mehak, John D. Kelleher, Michael Guilfoyle and Maria Chiara Leva
Machines 2024, 12(1), 45; https://doi.org/10.3390/machines12010045 - 9 Jan 2024
Cited by 1 | Viewed by 2095
Abstract
Human–robot teaming (HrT) is being adopted in an increasing range of industries and work environments. Effective HrT relies on the success of complex and dynamic human–robot interaction. Although it may be optimal for robots to possess all the social and emotional skills to [...] Read more.
Human–robot teaming (HrT) is being adopted in an increasing range of industries and work environments. Effective HrT relies on the success of complex and dynamic human–robot interaction. Although it may be optimal for robots to possess all the social and emotional skills to function as productive team members, certain cognitive capabilities can enable them to develop attitude-based competencies for optimizing teams. Despite the extensive research into the human–human team structure, the domain of HrT research remains relatively limited. In this sense, incorporating established human–human teaming (HhT) elements may prove practical. One key element is mutual performance monitoring (MPM), which involves the reciprocal observation and active anticipation of team members’ actions within the team setting, fostering enhanced team coordination and communication. By adopting this concept, this study uses ML-based visual action recognition as a potential tool for developing an effective way to monitor the human component in HrT. This study utilizes a data modeling approach on an existing dataset, the “Industrial Human Action Recognition Dataset” (InHARD), curated specifically for human action recognition assembly tasks in industrial environments involving human–robot collaborations. This paper presents the results of this modeling approach in analyzing the dataset to implement a theoretical concept that can be a first step toward enabling the system to adapt dynamically. The outcomes emphasize the significance of implementing state-of-the-art team concepts by integrating modern technologies and assessing the possibility of advancing HrT in this direction. Full article
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21 pages, 6000 KiB  
Article
Considerations on the Dynamics of Biofidelic Sensors in the Assessment of Human–Robot Impacts
by S. M. B. P. B. Samarathunga, Marcello Valori, Rodolfo Faglia, Irene Fassi and Giovanni Legnani
Machines 2024, 12(1), 26; https://doi.org/10.3390/machines12010026 - 30 Dec 2023
Viewed by 1655
Abstract
Ensuring the safety of physical human–robot interaction (pHRI) is of utmost importance for industries and organisations seeking to incorporate robots into their workspaces. To address this concern, the ISO/TS 15066:2016 outlines hazard analysis and preventive measures for ensuring safety in Human–Robot Collaboration (HRC). [...] Read more.
Ensuring the safety of physical human–robot interaction (pHRI) is of utmost importance for industries and organisations seeking to incorporate robots into their workspaces. To address this concern, the ISO/TS 15066:2016 outlines hazard analysis and preventive measures for ensuring safety in Human–Robot Collaboration (HRC). To analyse human–robot contact, it is common practice to separately evaluate the “transient” and “quasi-static” contact phases. Accurately measuring transient forces during close human–robot collaboration requires so-called “biofidelic” sensors that closely mimic human tissue properties, featuring adequate bandwidth and balanced damping. The dynamics of physical human–robot interactions using biofidelic measuring devices are being explored in this research. In this paper, one biofidelic sensor is tested to analyse its dynamic characteristics and identify the main factors influencing its performance and its practical applications for testing. To this aim, sensor parameters, such as natural frequency and damping coefficient, are estimated by utilising a custom physical pendulum setup to impact the sensor. Mathematical models developed to characterise the sensor system and pendulum dynamics are also disclosed. Full article
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20 pages, 3042 KiB  
Article
Development of a Neuroergonomic Assessment for the Evaluation of Mental Workload in an Industrial Human–Robot Interaction Assembly Task: A Comparative Case Study
by Carlo Caiazzo, Marija Savkovic, Milos Pusica, Djordje Milojevic, Maria Chiara Leva and Marko Djapan
Machines 2023, 11(11), 995; https://doi.org/10.3390/machines11110995 - 26 Oct 2023
Cited by 3 | Viewed by 2189
Abstract
The disruptive deployment of collaborative robots, named cobots, in Industry 5.0 has brought attention to the safety and ergonomic aspects of industrial human–robot interaction (HRI) tasks. In particular, the study of the operator’s mental workload in HRI activities has been the research object [...] Read more.
The disruptive deployment of collaborative robots, named cobots, in Industry 5.0 has brought attention to the safety and ergonomic aspects of industrial human–robot interaction (HRI) tasks. In particular, the study of the operator’s mental workload in HRI activities has been the research object of a new branch of ergonomics, called neuroergonomics, to improve the operator’s wellbeing and the efficiency of the system. This study shows the development of a combinative assessment for the evaluation of mental workload in a comparative analysis of two assembly task scenarios, without and with robot interaction. The evaluation of mental workload is achieved through a combination of subjective (NASA TLX) and real-time objective measurements. This latter measurement is found using an innovative electroencephalogram (EEG) device and the characterization of the cognitive workload through the brainwave power ratio β/α, defined after the pre-processing phase of EEG data. Finally, observational analyses are considered regarding the task performance of the two scenarios. The statistical analyses show how significantly the mental workload diminution and a higher level of performance, as the number of components assembled correctly by the participants, are achieved in the scenario with the robot. Full article
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12 pages, 4501 KiB  
Article
Modeling the Contact Force in Constrained Human–Robot Collisions
by Sebastian Herbster, Roland Behrens and Norbert Elkmann
Machines 2023, 11(10), 955; https://doi.org/10.3390/machines11100955 - 12 Oct 2023
Cited by 4 | Viewed by 1948
Abstract
Collaborative robots (cobots) become more and more important in industrial manufacturing as flexible companions, working side by side with humans without safety fences. A key challenge of such workplaces is to guarantee the safety of the human co-workers. The safeguarding Power and Force [...] Read more.
Collaborative robots (cobots) become more and more important in industrial manufacturing as flexible companions, working side by side with humans without safety fences. A key challenge of such workplaces is to guarantee the safety of the human co-workers. The safeguarding Power and Force Limiting, as specified by ISO 10218-2 and ISO/TS 15066, has the objective to protect humans against robot collisions by preventing the robot from exceeding biomechanical limits. Unintended contact such as collisions can occur under unconstrained spatial conditions (a human body part can move freely) or constrained spatial conditions (a human body part is pinched). In particular, collisions under constrained conditions involve a high risk of injury and thus require the robot to stop immediately after detecting the collision. The robot’s speed has a significant influence on its stopping behavior, though, and thus on the maximum collision forces that the robot can exert on the human body. Consequently, a safe velocity is required that avoids the robot from exerting forces and pressures beyond the biomechanical limits. Today, such velocities can only be ascertained in costly robot experiments. In this article, we describe a model that enables us to determine the contact forces of a cobot as they occur in constrained collisions. Through simulations, it becomes possible to iteratively determine the maximum safe velocity for a specific contact hazard that occurs under constrained spatial conditions. Experimental tests with different cobots confirm the results of our model, albeit not for all robots. Despite the mixed test results, we strongly believe that our model can significantly improve the reliability of assumptions made today during the planning of cobots. Full article
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