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In robotic contour-following tasks, such as sewing or cutting, an industrial robot guides a tool along the contour of a workpiece. Manually teaching the robot is time consuming and results in a system that is unable to react to uncertainties or changes in the environment. Because the cost effectiveness of a robotic solution depends on the amount of human intervention, particularly small series production benefits from greater system autonomy through the integration of sensor systems. In this paper, we present an integrated approach for multisensor contour following. A look-ahead vision sensor steers the robot along the workpiece while force-feedback control maintains the desired contact force. Acceleration sensors are used to compensate the force measurements for inertial forces, so the arrangement of the acceleration sensors is investigated. Couplings that arise between force and vision control systems are estimated, and online measurements of contact forces between the robot and the environment are used to adjust measurement results from the vision sensor to compensate for environmental deformations. Parameters of a second-order linear model of the environment are estimated by online identification. The identification combines force and acceleration sensors in an observer-based control scheme. The system is validated by experiments that involve contour following on compliant objects.
Koch et al. (Mon,) studied this question.
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