Article
Chemistry, Analytical
Andrea Pupa, Wietse Van Dijk, Christiaan Brekelmans, Cristian Secchi
Summary: This paper proposes an online framework to address task scheduling challenges in collaborative robotics, specifically in an industrial setting, by handling uncertainties and promoting parallel human-robot work.
Article
Robotics
Cheng Fang, Luka Peternel, Ajay Seth, Massimo Sartori, Katja Mombaur, Eiichi Yoshida
Summary: The advancement of human modeling and robotics have common interests and interconnections. The principles used in robotics, such as multibody dynamics and control theory, have greatly benefited human modeling. With the development of safer and smarter robots, they actively participate in our lives and assist us. By combining human modeling and robotic methods in physical human-robot interaction, it can lead to improved human understanding and functional assistance.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2023)
Article
Robotics
Mario Selvaggio, Marco Cognetti, Stefanos Nikolaidis, Serena Ivaldi, Bruno Siciliano
Summary: Sharing control of a robotic system with an autonomous controller allows humans to reduce cognitive and physical workload during tasks, and recent developments in inference and learning techniques have expanded the applications of shared control approaches. This enables robotic systems to seamlessly adapt their autonomy levels. This letter compiles the latest research results in shared control and shared autonomy, with a focus on physical human-robot interaction, discussing architectures and methods developed for shared control and shared autonomy. The letter concludes with a discussion on open issues.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Article
Automation & Control Systems
Elisa Prati, Valeria Villani, Fabio Grandi, Margherita Peruzzini, Lorenzo Sabattini
Summary: This article proposes a new method for designing collaborative robotic systems with a focus on interaction characteristics, emphasizing the interaction experience through a user-centered approach. Through two industrial case studies, the applicability of this method to real-world domains is showcased.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2022)
Article
Computer Science, Interdisciplinary Applications
Debasmita Mukherjee, Kashish Gupta, Li Hsin Chang, Homayoun Najjaran
Summary: In response to increased global competition, manufacturers are required to be more flexible in meeting customer demands, leading to the introduction of human operators and robots for their respective strengths, with a growing interest in shared human-robot workspace. Research in industrial human-robot collaboration focuses on human-robot safety, collaboration modes, and robot autonomy and adaptability.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2022)
Article
Engineering, Biomedical
Christian Tamantini, Francesca Cordella, Clemente Lauretti, Francesco Scotto di Luzio, Benedetta Campagnola, Laura Cricenti, Marco Bravi, Federica Bressi, Francesco Draicchio, Silvia Sterzi, Loredana Zollo
Summary: This paper presents a psychophysiological-aware control strategy for upper limb robot-aided orthopedic rehabilitation, which can adapt treatments to patients' needs. The strategy has three main features: i) generating point-to-point trajectories inside an adaptable workspace, ii) providing assistance in guiding patients' limbs, allowing them to move with spatial and temporal autonomy, and iii) tuning control parameters based on patients' kinematics performance and psychophysiological state. The strategy has been validated in a clinical setting and shown to have a positive impact on participants, leading to improved motor functions.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
(2023)
Review
Computer Science, Information Systems
S. M. Bhagya P. Samarakoon, M. A. Viraj J. Muthugala, A. G. Buddhika P. Jayasekara
Summary: An emerging trend of using service robots in various applications is seen as a promising effort to improve the quality of life. These robots are designed for non-expert users and often need to navigate in environments with humans. Therefore, it is important for these robots to exhibit human-friendly navigation behavior. This paper presents a review on Human-Robot Proxemics (HRP), including user studies and methods for establishing HRP awareness in service robots. The review identifies limitations in current state-of-the-art research and suggests potential future work. Additionally, it summarizes important HRP parameters and behavior from existing user studies, providing valuable data for developing HRP-aware behavior in service robots.
Article
Robotics
Nuria Pena Perez, Jonathan Eden, Ekaterina Ivanova, Etienne Burdet, Ildar Farkhatdinov
Summary: By perturbing the haptic and visual feedback of the right hand, the effort distribution between the two hands can be altered. Visual disturbance was more effective in causing participants to rely solely on their unperturbed hand.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Robotics
Tsung-Ren Huang, Yu-Wei Liu, Shin-Min Hsu, Joshua O. S. Goh, Yu-Ling Chang, Su-Ling Yeh, Li-Chen Fu
Summary: Personal psychological variables are valuable for personalized human-robot interactions. This study demonstrated the validity of embedding psychological test questions into casual conversations for user profiling, with strong correlation in young adults but only moderate in older populations. It suggests caution when applying this testing method to older adults or other special populations.
INTERNATIONAL JOURNAL OF SOCIAL ROBOTICS
(2021)
Article
Chemistry, Multidisciplinary
Harsh Maithani, Juan Antonio Corrales Ramon, Laurent Lequievre, Youcef Mezouar, Matthieu Alric
Summary: This study demonstrates a proof of concept of a physical human-robot interaction-based assistive strategy for an industrial meat cutting system, which can potentially be transferred to an exoskeleton. The research focuses on how a robot can assist a human in meat processing, specifically in the meat cutting industry, by developing two assistive strategies and integrating them into an impedance controller.
APPLIED SCIENCES-BASEL
(2021)
Article
Robotics
Marta Lagomarsino, Marta Lorenzini, Merryn Dale Constable, Elena De Momi, Cristina Becchio, Arash Ajoudani
Summary: This letter investigates the possibility of applying the cognitive science principle of humans acting coefficiently as a group to human-robot cooperative tasks, aiming to promote more seamless and natural interaction. A modelling approach is proposed to capture the implicit indicators of human comfort and discomfort, as well as robot energy consumption, in order to measure human-robot coefficiency. Reinforcement learning is then employed to adapt and learn the combination of robot interaction parameters that maximize such coefficiency. The results demonstrate that by acting coefficiently, the robot can meet individual preferences, improve human comfort, and foster trust in the robotic partner.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2023)
Article
Computer Science, Interdisciplinary Applications
Luca Gualtieri, Erwin Rauch, Renato Vidoni
Summary: This study presents a systematic methodology for static allocation of assembly tasks between humans and robots, considering a human-centric approach and requirements in terms of technical feasibility, safety and ergonomics, quality, and economics. It helps manufacturers overcome technical barriers and implement more sustainable, high-quality, and efficient manufacturing processes.
INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING
(2023)
Article
Robotics
Matthew Story, Phil Webb, Sarah R. Fletcher, Gilbert Tang, Cyril Jaksic, Jon Carberry
Summary: The study finds that the speed and proximity setting of an industrial robot arm can impact a person's workload, but their effect on trust is not significant. It highlights the importance of considering these factors in the development and design of collaborative work cells.
INTERNATIONAL JOURNAL OF SOCIAL ROBOTICS
(2022)
Article
Robotics
Robin Jeanne Kirschner, Henning Mayer, Lisa Burr, Nico Mansfeld, Saeed Abdolshah, Sami Haddadin
Summary: In this study, the Expectable Motion Unit (EMU) is proposed to prevent sudden, uncontrolled motions in human-robot interaction (HRI). By establishing a mapping between robot velocity, robot-human distance, and the relative frequency of involuntary motions (IM), the robot's speed during task execution is limited in real-time. The EMU is integrated into a holistic safety framework that considers both physical and psychological safety knowledge.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Robotics
Luis F. C. Figueredo, Rafael Castro Aguiar, Lipeng Chen, Samit Chakrabarty, Mehmet R. Dogar, Anthony G. Cohn
Summary: This study presents a new metric for calculating quality index in human manipulation and physical human-robot collaboration, addressing the gap in current research. The proposed solution combines pre-computation of biomechanics, ergonomics, muscle assessment, and joint constraints to simplify manipulability assessment for various applications. Numerical evidence shows that the analysis greatly outperforms previous results in terms of computing time without compromising performance.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Article
Robotics
Beatrice Capelli, Cristian Secchi, Lorenzo Sabattini
Summary: This letter proposes a new method based on energy-tank control and Control Barrier Functions to guarantee passivity in a controlled system. The goal is to achieve a desired behavior with minimal modification while ensuring passivity. The method is suitable for various applications and can modify behavior to enforce passivity when necessary.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Chemistry, Analytical
Andrea Pupa, Wietse Van Dijk, Christiaan Brekelmans, Cristian Secchi
Summary: This paper proposes an online framework to address task scheduling challenges in collaborative robotics, specifically in an industrial setting, by handling uncertainties and promoting parallel human-robot work.
Article
Automation & Control Systems
Federica Ferraguti, Chiara Talignani Landi, Andrew Singletary, Hsien-Chung Lin, Aaron Ames, Cristian Secchi, Marcello Bonfe
IEEE ROBOTICS & AUTOMATION MAGAZINE
(2022)
Article
Automation & Control Systems
Elisa Prati, Valeria Villani, Fabio Grandi, Margherita Peruzzini, Lorenzo Sabattini
Summary: This article proposes a new method for designing collaborative robotic systems with a focus on interaction characteristics, emphasizing the interaction experience through a user-centered approach. Through two industrial case studies, the applicability of this method to real-world domains is showcased.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2022)
Article
Automation & Control Systems
Valeria Villani, Lorenzo Sabattini, Giorgia Zanelli, Enrico Callegati, Benjamin Bezzi, Paulina Baranska, Zofia Mockallo, Dorota Zolnierczyk-Zreda, Julia N. Czerniak, Verena Nitsch, Alexander Mertens, Cesare Fantuzzi
Summary: With the advancement of production systems, there is an increasing demand for high-skilled labor and the complexity of human-machine interfaces has risen. Novel design approaches, such as adapting industrial HMIs to human operators' skills and capabilities, have been proposed. Evaluation results show that using adaptive interaction systems can improve workers' performance during tasks.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2022)
Article
Robotics
Federico Benzi, Maximilian Brunner, Marco Tognon, Cristian Secchi, Roland Siegwart
Summary: This research proposes an adaptive controller for stable and efficient physical interaction tasks with unmodeled and dynamic objects in unknown environments. The controller uses energy tanks and online parameter adaptation to guarantee robust stability.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Robotics
Federico Benzi, Federica Ferraguti, Giuseppe Riggio, Cristian Secchi
Summary: This article proposes an energy-based architecture for shared autonomy in robotic applications to ensure stability. By correctly translating high-level decisions into low-level control inputs, it can avoid unstable behavior.
IEEE TRANSACTIONS ON ROBOTICS
(2022)
Article
Computer Science, Artificial Intelligence
Valeria Villani, Cristian Secchi, Marco Lippi, Lorenzo Sabattini
Summary: Recent advances in robotics have made it possible for robots to assist and work together with humans. To promote their use and diffusion, intuitive and user-friendly interaction means should be adopted. Gestures have become an established way to interact with robots, and this article focuses on the problem of gesture recognition in human-robot interaction (HRI). The authors propose a pipeline framework that takes into account the specific constraints of HRI and evaluate its performance using standard machine learning algorithms.
IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS
(2023)
Article
Automation & Control Systems
Marco Minelli, Nicola Piccinelli, Fabio Falezza, Federica Ferraguti, Riccardo Muradore, Cristian Secchi
Summary: In this article, a novel bilateral teleoperation architecture for a multiarms system is proposed based on the two-layer approach. The passivity layer ensures the passivity of the overall architecture, while the transparency layer allows for the design of desired behavior. The concept of shared energy tank is exploited to improve energy efficiency and support both admittance and impedance causality robots. Additionally, a framework that combines teleoperated and autonomous robots is introduced and validated using the da Vinci research kit (dVRK) and an autonomous arm holding the endoscope in a realistic surgical scenario.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2023)
Article
Multidisciplinary Sciences
Federico Pratissoli, Andreagiovanni Reina, Yuri Kaszubowski Lopes, Carlo Pinciroli, Genki Miyauchi, Lorenzo Sabattini, Roderich Gross
Summary: The study demonstrates that simple self-propelled robotic modules can achieve accurate group navigation through deformable elastic links. By coupling the modules, soft-bodied aggregates can move and deform reliably, outperforming aggregates without or with rigid couplings. The findings highlight the importance of mechanical couplings in achieving coherent motion among individuals with limited and error-prone abilities, and suggest potential applications in low-power, stretchable robots for high-resolution monitoring and manipulation.
NATURE COMMUNICATIONS
(2023)
Article
Automation & Control Systems
Federico Pratissoli, Riccardo Brugioni, Nicola Battilani, Lorenzo Sabattini
Summary: This paper focuses on the coordination and traffic management of a group of Automated Guided Vehicles (AGVs) in real industrial scenarios. The proposed methodology is based on a three-layer control architecture, aiming to prevent congestion, collisions, and deadlocks. The coordination algorithm utilizes a novel deadlock prevention approach based on time-expanded graphs. Additionally, the presented control architecture addresses practical issues and proposes a flexible and robust methodology for multi-AGVs traffic-aware management.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Article
Robotics
Federico Benzi, Cristian Secchi
Summary: In this letter, the authors address the problem of adapting the behavior of a robot controller when interacting with unmodelled dynamic systems. They propose a framework that simultaneously adapts the admittance and power limits in the controller to ensure both safety and task performance.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2023)
Article
Ergonomics
Valeria Villani, Lorenzo Sabattini, Dorota Zolnierczyk-Zreda, Zofia Mockallo, Paulina Baranska, Cesare Fantuzzi
Summary: This article discusses the importance of measuring worker satisfaction in industrial automation, proposing a holistic model that includes adaptive automation and working conditions, along with a questionnaire as a practical tool for assessing worker satisfaction. The model takes into account psychosocial and physical working conditions and the characteristics of the automation system. The proposed questionnaire version has been adjusted based on pilot testing and end-user feedback from shop floor operators.
INTERNATIONAL JOURNAL OF OCCUPATIONAL SAFETY AND ERGONOMICS
(2021)
Article
Automation & Control Systems
Ran Jiao, Wenjie Liu, Ramy Rashad, Jianfeng Li, Mingjie Dong, Stefano Stramigioli
Summary: A novel end-effector bilateral rehabilitation robotic system (EBReRS) is developed for upper limb rehabilitation of patients with hemiplegia, providing simulations of multiple bimanual coordinated training modes, showing potential for application in home rehabilitation.
Article
Automation & Control Systems
Qiaosheng Pan, Yifang Zhang, Xiaozhu Chen, Quan Wang, Qiangxian Huang
Summary: A resonant piezoelectric rotary motor using parallel moving gears mechanism has been proposed and tested, showing high power output and efficiency.
