Teaching bimanual dexterous manipulations with interactive demonstrations and reinforcement learning

Robot dexterous manipulation research has drawn more attention in recent years since the development of various learning methods makes it possible for robots to achieve dexterity at the human level. Many attempts have been made to integrate human knowledge into Reinforcement Learning (RL) processes for faster learning speed and better...

Teaching Robots How to Grasp Like Humans by Humans: An Interactive Approach

Grasping objects in a smooth humanlike motion, instead of the more typical pick-and-place approach, includes multiple aspects that need to be performed correctly for a successful grasp. These aspects involve moving the end-effector such that its surface makes and retains contact with the object while also coordinating the movement of the gripper...

Learning Interactively to Resolve Ambiguity in Sensor Policy Fusion for Robot

This work applies interactive imitation learning for the navigation of a mobile robot. The algorithm"Learning Interactively to Resolve Ambiguity in Sensor Policy Fusion" (LIRA-SPF) is introduced in the field of machine learning for robot navigation. This algorithm extends on existing methods by allowing the ambiguity-free fusion of existing...