Dexterous Robotic Hand

Dexterous robotic hands aim to replicate the dexterity and adaptability of human hands for complex manipulation tasks, focusing on robust grasping and in-hand manipulation of diverse objects. Current research emphasizes developing control algorithms, often based on reinforcement learning and imitation learning, that enable robots to learn complex manipulation skills from both simulated and real-world data, often incorporating tactile and visual feedback. These advancements are significant because they pave the way for robots to perform a wider range of tasks in unstructured environments, impacting fields such as manufacturing, healthcare, and domestic assistance.