Learning Insertion Primitives with Discrete-Continuous Hybrid Action Space for Robotic Assembly Tasks
Xiang Zhang,Shiyu Jin,Changhao Wang,Xinghao Zhu,Masayoshi Tomizuka,Xiang Zhang,Shiyu Jin,Changhao Wang,Xinghao Zhu,Masayoshi Tomizuka
This paper introduces a discrete-continuous action space to learn insertion primitives for robotic assembly tasks. Primitives are sequences of elementary actions with certain exit conditions, such as “pushing down the peg until contact”. Since the primitive is an abstraction of robot control commands and encodes human prior knowledge, it reduces the exploration difficulty and yields better learnin...
