Fast-Learning Grasping and Pre-Grasping via Clutter Quantization and Q-map Masking
Dafa Ren,Xiaoqiang Ren,Xiaofan Wang,S. Tejaswi Digumarti,Guodong Shi,Dafa Ren,Xiaoqiang Ren,Xiaofan Wang,S. Tejaswi Digumarti,Guodong Shi
Grasping objects in cluttered scenarios is a challenging task in robotics. Performing pre-grasp actions such as pushing and shifting to scatter objects is a way to reduce clutter. Based on deep reinforcement learning, we propose a Fast-Learning Grasping (FLG) framework, that can integrate pre-grasping actions along with grasping to pick up objects from cluttered scenarios with reduced real-world t...
