Article
Robotics
Fatemeh Zahedi, Dongjune Chang, Hyunglae Lee
Summary: This letter introduces a user-adaptive variable damping controller that improves the overall performance of coupled human-robot systems during physical interaction. Bayesian optimization is used to evaluate and optimize the controller performance, considering the uncertainty of human behaviors and noisy observations. Experiments with a robotic arm manipulator show that the adaptive control strategy significantly reduces energy expenditure and improves stability, agility, and user effort.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Chemistry, Analytical
Tilen Brecelj, Tadej Petric
Summary: This paper addresses human-robot collaboration by applying a phase state system to a humanoid robot. The method proves to be a suitable way of controlling robots through physical human-robot interaction.
Article
Automation & Control Systems
Aigerim Nurbayeva, Almas Shintemirov, Matteo Rubagotti
Summary: This article proposes motion planning algorithms for industrial manipulators in the presence of human operators based on deep neural networks (DNNs), aimed at imitating the behavior of a nonlinear model predictive control (NMPC) scheme. The proposed DNN solutions retain the safety features of NMPC in terms of speed and separation monitoring, defined according to the guidelines in the ISO/TS 15066 standard. At the same time, they improve the robot performance in terms of task completion time, and of a posteriori evaluation of the NMPC cost function on experimental data. The reasons for this improvement are the reduced computational delay of running a DNN compared to solving the nonlinear programs associated to NMPC, and the ability to implicitly learn how to predict the human operator's motion from the training set.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Computer Science, Information Systems
Roman Michalik, Ales Janota, Michal Gregor, Marian Hrubos
Summary: This paper discusses an approach for controlling a cooperating YuMi robot using hand gestures recognized by a camera and artificial intelligence through a TCP/IP connection with Python. The program can be enhanced by integrating other IoT devices for robot control and data collection for specific applications.
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
Automation & Control Systems
Jacky Baltes, Guilherme Christmann, Saeed Saeedvand
Summary: This paper proposes a deep reinforcement learning algorithm to learn the steering control of a two-wheeled scooter. The algorithm is compared with a classical PID controller and achieves better results in balancing the scooter. The evaluation on a real robot and scooter shows the effectiveness of the proposed method in different control scenarios and speeds.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Xin Shu, Fenglei Ni, Xinyang Fan, Shuai Yang, Changyuan Liu, Baoxu Tu, Yiwei Liu, Hong Liu
Summary: Humanoid robots have attracted attention for their compatibility with human environments, but they still lack stability and reliability in real-world settings. Combining humanoid robots with various stable mobile platforms is a favored solution. This article presents a versatile humanoid robot platform, which allows flexible deployment in diverse scenarios by incorporating multimodal perception and extensible interfaces. The platform has achieved impressive integration, lightness, dexterity, and strength, with the goal of human-intelligent manipulation skills for human-engineered environments. The article elaborates on design choices, subsystems, and demonstrates the platform's performance through experiments.
CAAI TRANSACTIONS ON INTELLIGENCE TECHNOLOGY
(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
Computer Science, Artificial Intelligence
Shangke Lyu, Nithish Muthuchamy Selvaraj, Chien Chern Cheah
Summary: Traditional applications of robot manipulators are primarily focused on tracking control tasks, but advances in sensing and robotic technologies have led to the need for more complex tasks. This article proposes a task learning approach that uses task parameters of a potential energy function to learn human motion behaviors, and introduces a new robot controller for playback and combination of tasks.
IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS
(2022)
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
Computer Science, Artificial Intelligence
Maria Jose Pinto-Bernal, Nathalia Cespedes, Paola Castro, Marcela Munera, Carlos A. Cifuentes
Summary: There has been an increasing interest in using social robots as a support tool, particularly in the field of Autism treatments. This study focuses on developing and assessing a social robotic platform that promotes physical interaction. The results show that physical interaction does not significantly impact the patients' performance in activities, but it increases encouragement and motivation. Moreover, a substantial percentage of control group children express the intention to physically interact with the robot, indicating its importance as a means of communication.
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
(2022)
Article
Robotics
Johannes Lachner, Felix Allmendinger, Eddo Hobert, Neville Hogan, Stefano Stramigioli
Summary: This study investigates the certification process of applications with physical human-robot interaction (pHRI) and proposes controlling the robot's energy to ensure safety. By reducing the number of safety-related parameters, the proposed technique accelerates the commissioning of pHRI applications.
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
(2021)
Article
Robotics
Artemiy Oleinikov, Sanzhar Kusdavletov, Almas Shintemirov, Matteo Rubagotti
Summary: This letter proposes a nonlinear model predictive control (NMPC) approach for real-time planning of point-to-point motions of serial robot manipulators that share their workspace with a human. The NMPC law solves a nonlinear program online, based on a kinematic model, and guarantees safety by constraining the robot speed within the time-varying bounds determined by the speed-and-separation-monitoring (SSM) principle. Closed-loop stability is proven in detail, and the performance (in terms of productivity) of the proposed method is tested against standard SSM schemes via experiments on a Kinova Cen3 robot.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2021)
Article
Computer Science, Artificial Intelligence
Jonathan Cacace, Riccardo Caccavale, Alberto Finzi, Riccardo Grieco
Summary: This work considers a scenario where a human operator physically interacts with a collaborative robot to perform shared and structured tasks. The robotic system interprets human interventions and adjusts its behavior accordingly, based on the estimated operator intentions.
JOURNAL OF INTELLIGENT MANUFACTURING
(2023)
Article
Computer Science, Artificial Intelligence
Yue Hu, Naoko Abe, Mehdi Benallegue, Natsuki Yamanobe, Gentiane Venture, Eiichi Yoshida
Summary: This article explores the possibility of quantifying humans' physical and mental state during active physical interaction with a robot through a laboratory experiment. The study shows relationships between participants' physical and physiological data and their age, gender, perception, and personalities. Further developments can be made to implement an active physical human-robot interaction controller that considers both the physical and mental state of users.
IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS
(2022)
Article
Robotics
Abdellah Khelloufi, Nouara Achour, Robin Passama, Andrea Cherubini
Article
Automation & Control Systems
Zineb Abderrahmane, Gowrishankar Ganesh, Andre Crosnier, Andrea Cherubini
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2020)
Editorial Material
Robotics
Qiang Huang, Fumio Kanehiro, Tamim Asfour, Abderrahmane Kheddar, Zhuangguo Yu
INTERNATIONAL JOURNAL OF HUMANOID ROBOTICS
(2020)
Article
Robotics
Andrea Cherubini, Valerio Ortenzi, Akansel Cosgun, Robert Lee, Peter Corke
INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH
(2020)
Editorial Material
Robotics
Qiang Huang, Fumio Kanehiro, Tamim Asfour, Abderrahmane Kheddar, Zhangguo Yu
INTERNATIONAL JOURNAL OF HUMANOID ROBOTICS
(2020)
Editorial Material
Automation & Control Systems
Arash Ajoudani, Philipp Albrecht, Matteo Bianchi, Andrea Cherubini, Simona Del Ferraro, Philippe Fraisse, Lars Fritzsche, Manolo Garabini, Alberto Ranavolo, Patricia Helen Rosen, Massimo Sartori, Nikos Tsagarakis, Bram Vanderborght, Sascha Wischniewski
IEEE ROBOTICS & AUTOMATION MAGAZINE
(2020)
Article
Chemistry, Analytical
Alberto Ranavolo, Arash Ajoudani, Andrea Cherubini, Matteo Bianchi, Lars Fritzsche, Sergio Iavicoli, Massimo Sartori, Alessio Silvetti, Bram Vanderborght, Tiwana Varrecchia, Francesco Draicchio
Article
Computer Science, Artificial Intelligence
David Navarro-Alarcon, Jiaming Qi, Jihong Zhu, Andrea Cherubini
FRONTIERS IN NEUROROBOTICS
(2020)
Article
Robotics
Mohamed Djeha, Arnaud Tanguy, Abderrahmane Kheddar
IEEE ROBOTICS AND AUTOMATION LETTERS
(2020)
Article
Chemistry, Analytical
Osama Mazhar, Sofiane Ramdani, Andrea Cherubini
Summary: The paper proposes a unified framework for recognizing static and dynamic gestures using simple RGB vision, suitable for inexpensive human-robot interaction. By employing a pose-driven attention strategy and combining CNN with LSTM, the framework accurately predicts dynamic gestures of the performing person.
Proceedings Paper
Automation & Control Systems
Saeid Samadi, Stephane Caron, Arnaud Tanguy, Abderrahmane Kheddar
2020 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA)
(2020)
Proceedings Paper
Computer Science, Artificial Intelligence
Anastasia Bolotnikova, Sebastien Courtois, Abderrahmane Kheddar
2020 29TH IEEE INTERNATIONAL CONFERENCE ON ROBOT AND HUMAN INTERACTIVE COMMUNICATION (RO-MAN)
(2020)
Article
Robotics
Anastasia Bolotnikova, Sebastien Courtois, Abderrahmane Kheddar
IEEE ROBOTICS AND AUTOMATION LETTERS
(2020)
Article
Robotics
Nahuel Alejandro Villa, Johannes Englsberger, Pierre-Brice Wieber
IEEE ROBOTICS AND AUTOMATION LETTERS
(2019)
