Learning Hierarchies in Robotic Manipulation: Asymmetries in Sequential Pushing and Grasping
This paper investigates whether a natural learning hierarchy exists between pushing and grasping in robotic manipulation. Using a deep Q-network with a shared trunk and separate branches, we train five agents: Joint (both primitives simultaneously), PFG (push-only pretraining then frozen trunk, learn grasp), GFP (grasp...