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While teleoperation provides a possibility for a robot to operate at extreme conditions instead of a human, teleoperating a robot still demands a heavy mental workload from a human operator. Learning from demonstrations can reduce the human operator's burden by learning repetitive teleoperation tasks. However, one of challenging issues is that demonstrations via teleoperation are less consistent compared...
This paper explores learning of interaction force skills by human demonstration in dynamic interaction tasks. Skillful force regulation is required in many cases to achieve the goal of a task and at the same time, not to cause undesired stress on the manipulator or the object under manipulation which could result in physical failure. For example, manipulation of compliant objects with varying physical...
Physical cooperation with humans greatly enhances the capabilities of robotic systems when leaving standardized industrial settings. Our novel cognition-enabled control framework presented in this paper enables a robotic assistant to enrich its own experience by acquisition of human task knowledge during joint manipulation. Our robot incrementally learns semantic task structures during joint task...
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