A One-eyed Self Learning Robot
Ben J.A. Kr?ose, P. Patrick van der Smagt, and Frans C.A. Groen
Dept. of Computer Systems, University of Amsterdam
Kruislaan 403, NL-1098 SJ Amsterdam, The Netherlands
A self-learning, adaptive control system for a robot arm using a vision system in a feedback loop is described. The task of the control system is to position the end-effector as accurate as possible directly above a target object, so that it can be grasped. The camera of the vision system is positioned in the end-effector and the visual information is used directly to control the robot. Two strategies are presented to solve the problem of obtaining 3D information from a single camera: a) using the size of the target object and b) using information from a sequence of images from the moving camera. In both cases a neural network is trained to perform the desired mapping.
Conventional sensor-based control systems require explicit knowledge of the kinematics and dynamics of the robot and a careful calibration of the sensor
?This research has been partly sponsored by the Dutch Foundation for Neural Networks.