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Despite the availability in the literature of several constraint-based motion generation algorithms, modest attention has been paid to their robustness with respect to noise, and more in general, to unstructured uncertainties. Especially in the case of sensor-related constraints, the envisaged robustness properties are clearly crucial to enforce the correct and expected behaviour of these algorithms. This paper contributes with a method to explicitly account for different sources of uncertainty. We also suggest a computational efficient way to consistently modify the constraint specification in order to obtain such robustness. An experimental verification on a visual aided grasping task, where visibility of the object is to be maintained, enlightens the benefits of the proposed approach in terms of achieving the desired robustness.
Zanchettin et al. (Sat,) studied this question.