Online approach for altering robot behaviors based on human in the loop coaching gestures

The creation and adaptation of motor behaviors is an important capability for autonomous robots. In this paper we propose an approach for altering existing robot behaviors online, where a human coach interactively changes the robot motion to achieve the desired outcome. Using hand gestures, the human coach can specify the desired modifications to the previously acquired behavior. To preserve a natural posture while performing the task, the movement is encoded in the robot's joint space using periodic dynamic movement primitives. The coaching gestures are mapped to the robot joint space via robot Jacobian and used to create a virtual force field affecting the movement. A recursive least squares technique is used to modify the existing movement with respect to the virtual force field. The proposed approach was evaluated on a simulated three degrees of freedom planar robot and on a real humanoid robot, where human coaching gestures were captured by an RGB-D sensor. Although our focus was on rhythmic movements, the developed approach is also applicable to discrete (point-to-point) movements.