With the continuous progress of robotic research, robots play an increasingly important role in academic research and industry. However, the application and development of robots in a demanding environment with limited information and much unpredictability such as high-precision assembly, surgical operation, operation in deep space or ocean, rehabilitation, remote service, and remains hampered. Humans have an innate ability to perform these tasks with relative ease due to the integration and coordination of perception, decision, motion control, and the musculoskeletal system, even in demanding environments. Establishing human-inspired robotic intelligence and structures from the imitation of neural mechanisms to body structures may be a potential way to improve the performance of robots in demanding environments.
Based on the above observation, this Research Topic hopes to discuss how to select key mechanisms related to human performance and promote human-inspired robotic intelligence and structure with these neural mechanisms. This Research Topic will present recent advanced algorithms and applications within human-inspired robotic intelligence and structure in demanding environments, thereby providing a comprehensive overview for future directions in both theoretical and engineering aspects. Authors are encouraged to submit original research and review papers that present state-of-the-art research and applications of human-inspired robotic intelligence and structure in demanding environments.
Potential topics include but are not limited to the following:
- Brain-inspired motion control with fast response, high precision, and robustness under limited information and uncertain environments.
- Design and control of human mimetic robotic structures (e.g. musculoskeletal robots, artificial muscular actuators, etc.).
- Skill learning in robot-assistive surgery and human-robot interaction.
- Brain-inspired visual cognition with lightweight model, robustness.
- Brain-inspired decision-making of robots in complex and uncertain environments.
- Integrations of visual cognition, decision making, and motion control.
- Dexterous manipulation in demanding environments.
- Telerobotics in demanding environments.
With the continuous progress of robotic research, robots play an increasingly important role in academic research and industry. However, the application and development of robots in a demanding environment with limited information and much unpredictability such as high-precision assembly, surgical operation, operation in deep space or ocean, rehabilitation, remote service, and remains hampered. Humans have an innate ability to perform these tasks with relative ease due to the integration and coordination of perception, decision, motion control, and the musculoskeletal system, even in demanding environments. Establishing human-inspired robotic intelligence and structures from the imitation of neural mechanisms to body structures may be a potential way to improve the performance of robots in demanding environments.
Based on the above observation, this Research Topic hopes to discuss how to select key mechanisms related to human performance and promote human-inspired robotic intelligence and structure with these neural mechanisms. This Research Topic will present recent advanced algorithms and applications within human-inspired robotic intelligence and structure in demanding environments, thereby providing a comprehensive overview for future directions in both theoretical and engineering aspects. Authors are encouraged to submit original research and review papers that present state-of-the-art research and applications of human-inspired robotic intelligence and structure in demanding environments.
Potential topics include but are not limited to the following:
- Brain-inspired motion control with fast response, high precision, and robustness under limited information and uncertain environments.
- Design and control of human mimetic robotic structures (e.g. musculoskeletal robots, artificial muscular actuators, etc.).
- Skill learning in robot-assistive surgery and human-robot interaction.
- Brain-inspired visual cognition with lightweight model, robustness.
- Brain-inspired decision-making of robots in complex and uncertain environments.
- Integrations of visual cognition, decision making, and motion control.
- Dexterous manipulation in demanding environments.
- Telerobotics in demanding environments.
