Predictive sensor guided robotic manipulators in automated welding cells

This paper presents an on-line tracking optimization scheme for sensor guided robotic manipulators by associating sensor information, manipulator dynamics and a path generator model. Feedback linearization-decoupling permits the use of linear SISO prediction models for the dynamics of each robot joint. Scene interpretation of CCD-camera images generates spline fitted segments of future trajectory. In the sensor vision field the proposed optimization criteria minimizes the error between state variables of the prediction model and the state variables of the spline trajectory generator. These techniques, allied with separation of disturbance rejection and path-tracking performance by the proposed feed-forward following model predictive (FMP) servo-controller design, permits very high path tracking dynamics (and consequently small errors). Experimental results on implementation of a CCD-camera guided hydraulic robot and a welding robot demonstrates the practical relevance of the proposed approach.