Papers Published

  1. Prabhu, S.M. and Garg, D.P., Fuzzy reinforcement compliance control for robotic assembly, Proceedings of the 1995 IEEE International Symposium on Intelligent Control (Cat. No.95CH35815) (1995), pp. 623 - 8 [ISIC.1995.525124] .
    (last updated on 2007/04/10)

    Compliance inherently involves modification of the robot trajectory based on the contact forces occurring during the motion and enables the robot to perform a variety of manipulation tasks which require fine motion skills. Learning of active compliance behavior can endow a robot with some form of autonomous intelligence which can be very useful for the control of manipulators working in a partially known environment and for manufacturing automation. This paper reports on the acquisition of robot fine motion skills by means of learning a compliance control strategy using fuzzy reinforcement learning. The fuzzy reinforcement compliance controller is applied to a typical robotic assembly task and its performance is compared with other learning controllers

    assembling;compliance control;force control;fuzzy control;fuzzy logic;industrial manipulators;learning (artificial intelligence);manipulators;nonlinear control systems;position control;