Grasp torque control based on experiential learning and haptic feedback / 医疗卫生装备

ABSTRACT

Objective To propose a grasp torque control based on experimental learning and haptic feedback to facilitate the manipulator in dexterous manipulation.Methods An experience database was built firstly,and then the object was recognized by tactile feedback in the grasp task.If the object had been experitentially grasped,the torque was output based on the database.In case a new object was grasped,the optimal output torque was calculated by iterative learning.Results The experiment showed that the robot hand could find the experiential output torque quickly when encountering the object in database and calculate the torque by iterative learning to achieve grasp task.Conclusion The experiential database grows up when the robot hand learns more and more experience.It can fast output torque like human in the grasp task.