Soft Robotic Hand

Soft robotic hands aim to create dexterous, safe, and adaptable robotic manipulators inspired by human hands. Current research emphasizes developing lightweight, comfortable designs often using pneumatic actuation and textile materials, incorporating advanced tactile sensing (including vision-based approaches), and employing machine learning techniques like reinforcement learning and imitation learning to improve control and dexterity. These advancements are significant for applications in assistive robotics (e.g., rehabilitation), teleoperation, and manufacturing, offering potential for improved human-robot interaction and more versatile robotic manipulation.