Abstract

Background: Traditionally, robots perform desired tasks with the aid of end-users analytically decomposing and manually programming. Robots controlled the program can only follow program instructions to move, which bring great difficulty to non-professional users. So it is meaningful to study new robot control paradigm for robots to accomplish tasks actively without the professional program. Vision-based robot learning by demonstration (vision-based LbD) is an effective approach that a robot can autonomously accomplish a task with help of the combination of the learning by demonstration (LbD) and vision sensing technology. Vision-based LbD allows robots to learn skills through ‘seeing’ demonstrations of users with vision sensors. Vision-based LbD reduces the operation difficulty of robots and provides an intuitive manner for human interact with robot, especially for those users who have no professional program experience.

Objective: Providing the references for researchers who work in related fields by reviewing recent advances of vision-based LbD.

Methods: This paper reviews the latest patents and current representative articles related to visionbased LbD. The key methods of these references are introduced in the aspects of algorithms, innovations and principles.

Results: The researches related to vision-based LbD in the last 5 years are classified, the advantages of different algorithms in these patents and articles are introduced and analyzed, the future developments and potential problems in this field are discussed.

Conclusion: The main advantage of vision-based LbD is to allow users training robots for new tasks by the demonstration under the vision sensor without programming control. So, vision-based LbD provides an intuitive manner of robot learning by demonstration to solve the problem of human-robot interaction. Further improvement is required in the following aspects: Algorithm innovation, multiple demonstrations, many definitions of human action and so on. More patents on vision-based LbD should be invented.

Keywords: Human-robot interaction, imitation learning, robot imitation, robot learning algorithm, robot learning by demonstration, vision-based teaching.