An Integrated Vision-Based Robotic Arm Control Framework for Imitation Learning and Online Adaptive Robot Manipulation

This video demonstration paper presents an integrated vision-based control framework for imitation learning and adaptive manipulation control of robot arms. It addresses the challenges of programming robot skills for industrial applications. The results illustrate that the framework enables our robotic arm system to passively observe user demonstrations and imitate the demonstrated (complex) trajectories in pick-and-place tasks. Furthermore, the robot can automatically adapt its motion on the fly to a change in the target position (placement) and avoid an obstacle.