In this paper, we present a new vision-based method to control the shape of elastic rods with robot manipulators. Our new method computes parameterized regression features from online sensor measurements that enable to automatically quantify the objects configuration and establish an explicit shape servo-loop. To automatically deform the rod into a desired shape, our adaptive controller iteratively estimates the differential transformation between the robots motion and the relative shape changes; This valuable capability allows to effectively manipulate objects with unknown mechanical models. An auto-tuning algorithm is introduced to adjust the robots shaping motion in real-time based on optimal performance criteria. To validate the proposed theory, we present a detailed numerical and experimental study with vision-guided robotic manipulators.
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