Combined perception, control, and learning for teleoperation: Key technologies, applications, and challenges

Abstract

Teleoperation provides a promising way for human-robot collaboration in the unknown or unstructured environments to perform a cooperative task. It enables humans to complete a task at a remote side and combines both the human's intelligence and the robots' capabilities in a collaborative task. Therefore, it is necessary to conduct cross researches in terms of robotics, artificial intelligence, sensors, and mechatronics. This study covers the state-of-the-arts research in terms of perception, control, and learning. In this review, key technologies about information perception mechanism, control algorithms, human-robot interface, and robot learning strategies for teleoperation are introduced. Then, a comprehensive survey is summarised in representative applications in teleoperation, and the existing challenges and potential directions of the development are discussed.