About this Research Topic
Safety–critical processes in unpredictable environments require human intervention to assist or execute tasks that autonomous robots are not yet capable of handling. In diverse environments, the increased levels of autonomy for robots demand human–machine interaction to be safer, more intuitive, comfortable, and robust. Supervised autonomy - the robot’s autonomy supervised by humans - bridges the gap between teleoperated robotics and full autonomy. By automating specific tasks while keeping humans in the loop, supervised autonomy can enhance the safety and productivity of individuals, including workers, users, and patients, while providing operators with the ability to intervene when necessary. Human-robot interaction, collaboration and role adaptation during human-robot cooperation are characterized by different aspects that go from the body to the brain of the robot facilitated through communication interfaces. Our workshop, Supervised Autonomy: How to Shape Human-Robot Interaction from the Body to the Brain intends to investigate the influence of all those aspects on the realization of supervised autonomy in robots operating in different domains, such as driving, flying, assistive technologies, tele-operation, medical applications, logistics, manufacturing. How to shape human-robot "InterAction" is a question to be answered by focusing on the integrated “Phygital” aspects concerning sensors, design and materials, control and artificial intelligence.
This Research Topic will drive the creation of new points of view related to human-robot interaction overcoming the concept of human-robot shared control and human-robot collaboration. Above all, supervised autonomy, defined as the robot’s autonomy supervised by humans, is a complex and timely concept that involves all aspects of a robotic system, from the body to the brain. We believe that such a holistic and complete observation of the problem is new and urgently needed by the robotics research community.
Some of the questions we will try to answer are:
● How design, materials and control interfaces can help in realizing effective human supervision of robotic systems
● How human experience and lifelong learning can help to develop new paradigms for supervised autonomy
● How vision and tactile information together with AI-based elaboration of the information can be integrated in the learning process and in control strategies
● How neural control of movement between humans and robots can be realized and integrated in supervised autonomous systems
The core topics of interest are:
● Innovative materials for soft/rigid robots
● Hardware and software solutions for human-robot communication interfaces
● Learning visual representations for perception-action systems
● Vision and force integration for control of manipulation systems
● Reinforcement learning and adaptive control
● Interactive learning and lifelong learning
● Simulations for design and control
● Robotics applications across varied domains: driving, flying, assistive technologies, teleoperation, medical applications, logistics, and manufacturing.
This Research Topic is linked to the workshop of the same name that will be hosted on Friday 17th May at the 2024 IEEE International Conference on Robotics and Automation in Yokohama, Japan. We welcome contributions from workshop contributors and those who did not contribute to the workshop. Any contributions presented at the workshop must be extended to include 30% original content in order to be considered for publication.
This Research Topic will drive the creation of new points of view related to human-robot interaction overcoming the concept of human-robot shared control and human-robot collaboration. Above all, supervised autonomy, defined as the robot’s autonomy supervised by humans, is a complex and timely concept that involves all aspects of a robotic system, from the body to the brain. We believe that such a holistic and complete observation of the problem is new and urgently needed by the robotics research community.
Some of the questions we will try to answer are:
● How design, materials and control interfaces can help in realizing effective human supervision of robotic systems
● How human experience and lifelong learning can help to develop new paradigms for supervised autonomy
● How vision and tactile information together with AI-based elaboration of the information can be integrated in the learning process and in control strategies
● How neural control of movement between humans and robots can be realized and integrated in supervised autonomous systems
The core topics of interest are:
● Innovative materials for soft/rigid robots
● Hardware and software solutions for human-robot communication interfaces
● Learning visual representations for perception-action systems
● Vision and force integration for control of manipulation systems
● Reinforcement learning and adaptive control
● Interactive learning and lifelong learning
● Simulations for design and control
● Robotics applications across varied domains: driving, flying, assistive technologies, teleoperation, medical applications, logistics, and manufacturing.
This Research Topic is linked to the workshop of the same name that will be hosted on Friday 17th May at the 2024 IEEE International Conference on Robotics and Automation in Yokohama, Japan. We welcome contributions from workshop contributors and those who did not contribute to the workshop. Any contributions presented at the workshop must be extended to include 30% original content in order to be considered for publication.
Keywords: Robot, Materials, Hardware, Software, Soft, Rigid, HRI, Human-Robot Interaction, Communication Interface, Learning, Visual Representation, Manipulation, Perception-Action Systems
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
