A modular system for robust positioning using feedback from stereo vision

This paper introduces a modular framework for robot motion control using stereo vision, The approach is based on a small number of generic motion control operations referred to as primitive skills, Each primitive skill uses visual feedback to enforce a specific task-space kinematic constraint between a robot end-effector and a set of target features, By observing both the end-effector and target features, primitive skills are able to position with an accuracy that is independent of errors in hand-eye calibration. Furthermore, primitive skills are easily combined to form more complex kinematic constraints as required by different applications, These control laws have been integrated into a system that performs tracking and control on a single processor at real-time rates, Experiments with this system have shown that it is extremely accurate, and that it is insensitive to camera calibration error, The system has been applied to a number of example problems, showing that modular, high precision, vision-based motion control is easily achieved with off-the-shelf hardware.