Dexterous Hand

Dexterous hand research aims to create robotic hands capable of human-like manipulation, focusing on complex grasping, object manipulation in cluttered environments, and in-hand object manipulation of deformable objects. Current research heavily utilizes reinforcement learning, often incorporating neural networks (including LSTM-GRU hybrids) for control and point cloud data for object recognition, alongside advanced tactile sensing for improved dexterity. These advancements hold significant potential for applications in robotics, human-computer interaction, and assistive technologies, particularly by enabling robots to perform intricate tasks currently beyond their capabilities.