A Grasp Pose is All You Need: Learning Multi-Fingered Grasping with Deep Reinforcement Learning from Vision and Touch
Federico Ceola,Elisa Maiettini,Lorenzo Rosasco,Lorenzo Natale,Federico Ceola,Elisa Maiettini,Lorenzo Rosasco,Lorenzo Natale
Multi-fingered robotic hands have potential to enable robots to perform sophisticated manipulation tasks. However, teaching a robot to grasp objects with an anthropomorphic hand is an arduous problem due to the high dimensionality of state and action spaces. Deep Reinforcement Learning (DRL) offers techniques to design control policies for this kind of problems without explicit environment or hand...
