Human-in-the-loop Learning and Control for Robot Teleoperation presents recent, research progress on teleoperation and robots, including human-robot interaction, learning and control for teleoperation with many extensions on intelligent learning techniques. The book integrates cutting-edge research on learning and control algorithms of robot teleoperation, neural motor learning control, wave variable enhancement, EMG-based teleoperation control, and other key aspects related to robot technology, presenting implementation tactics, adequate application examples and illustrative interpretations.
Robots have been used in various industrial processes to reduce labor costs and improve work efficiency. However, most robots are only designed to work on repetitive and fixed tasks, leaving a gap with the human desired manufacturing effect.
Table of Contents1. Introduction
2. Software systems and platforms for teleoperation
3. Uncertainties compensation-based teleoperation control
4. User experience-enhanced teleoperation control
5. Shared control for teleoperation
6. Human-robot interaction in teleoperation systems
7. Task learning of teleoperation robot systems