Transforming sensor data to increase robustness in the control of calibration-free robots

In vision-based robot control typically more sensor data are available than the minimum necessary for computing robot control commands. We propose an approach for utilizing the redundant sensor data to improve the robustness of robot control. The key point is that the sensor data space is transformed into a space of lower dimensionality before computing the robot control commands, thus avoiding to solve an over-determined system of equations. Compared to the rather simple alternative method of truncating measurements it has the advantage that, in the interest of robustness, it takes into account all available measurements. The approach has been evaluated in real-world manipulation experiments with a calibration-free robot. It has proven to be suitable for a real-time implementation and has led to a more robust control than the alternative approach