Learning Periodic Tasks from Human Demonstrations
Jingyun Yang,Junwu Zhang,Connor Settle,Akshara Rai,Rika Antonova,Jeannette Bohg,Jingyun Yang,Junwu Zhang,Connor Settle,Akshara Rai,Rika Antonova,Jeannette Bohg
We develop a method for learning periodic tasks from visual demonstrations. The core idea is to leverage periodicity in the policy structure to model periodic aspects of the tasks. We use active learning to optimize parameters of rhythmic dynamic movement primitives (rDMPs) and propose an objective to maximize the similarity between the motion of objects manipulated by the robot and the desired mo...
