Title :
A connection network for robotic gripper control
Author :
Horne, Bill ; Jamshidi, M.
Author_Institution :
CAD Lab. Syst./Robotics, Albuquerque, NM, USA
Abstract :
A memory-based robotic control paradigm which learns relationships between a control effort and a change of state is introduced. It has been used to develop a learning control system which implements step responses in one dimension on a robotic gripper, with partial success. It was found that velocity as well as positional feedback were required to complete even simple movements. It is believed that aspects of this approach would readily extend to a tactile sensing system
Keywords :
artificial intelligence; learning systems; position control; robots; step response; AI; artificial intelligence; connection network; learning control system; memory-based robotic control; positional feedback; robotic gripper control; step responses; Acceleration; Control systems; Grippers; Mathematical model; Nonlinear equations; Orbital robotics; Robot control; Robot kinematics; Robot sensing systems; Torque control;
Conference_Titel :
Decision and Control, 1988., Proceedings of the 27th IEEE Conference on
Conference_Location :
Austin, TX
DOI :
10.1109/CDC.1988.194482
