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We present an assistance system that reasons about a human's intended actionsduring robot teleoperation in order to provide appropriate corrections forunintended behavior. We model the human's physical interaction with a controlinterface during robot teleoperation and distinguish between intended andmeasured physical actions explicitly. By reasoning over the unobservedintentions using model-based inference techniques, our assistive systemprovides customized corrections on a user's issued commands. We validate ouralgorithm with a 10-person human subject study in which we evaluate theperformance of the proposed assistance paradigms. Our results show that theassistance paradigms helped to significantly reduce task completion time,number of mode switches, cognitive workload, and user frustration and improveoverall user satisfaction.

Customized Handling of Unintended Interface Operation in Assistive Robots