Learning Dextrous Manipulation Skills for MultifingeredRobot Hands Using the Evolution Strategy
Machine Learning - Special issue on learning in autonomous robots
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In this paper we present a kinematic method for 6-degree-of-freedom manipulation of rigid objects using a dextrous robotic hand. Our method requires no prior models of the objects being manipulated; instead it obtains all the information needed directly from the hand''s sensors. Its low computational cost makes real-time performance easy to achieve. .pp We present experimental results showing the implementation of our method using the Utah/MIT dextrous hand. We also show that adding a Cartesian controller significantly improves the accuracy of the manipulation.