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Automating assembly processes outside controlled factory environments is still rare, mostly because of the inherent position uncertainties. The use of compliant motions allows robustness against the uncertainty, but automatic planning of compliant motion sequences is not computationally feasible. In this paper, we show how compliant assembly motions can be learned from human demonstrations. A human...
Learning to perform tasks like pulling a door handle or pushing a button, inherently easy for a human, can be surprisingly difficult for a robot. A crucial problem in these kinds of in-contact tasks is the context specificity of pose and force requirements. In this paper, a robot learns in-contact tasks from human kinesthetic demonstrations. To address the need to balance between the position and...
Kinesthetic teaching is an established method of teaching robots new skills without requiring robotics or programming knowledge. However, the inertia and uncoordinated motions of individual joints decrease the intuitiveness and naturalness of interaction and impair the quality of the learned skill. This paper proposes a method to ease kinesthetic teaching by combining the idea of incremental learning...
This paper demonstrates a method for simultaneous transfer of positional and force requirements for in-contact tasks from a human instructor to a robotic arm through kinesthetic teaching. This is achieved by a specific use of the sensory configuration, where a force/torque sensor is mounted between the tool and the flange of a robotic arm endowed with integrated torque sensors at each joint. The human...
We present a (generalizable) method aimed to simultaneously transfer positional and force requirements encoded in a physical human skill (wood planing) from a human instructor to a robotic arm through kinesthetic teaching. We achieve our goal through a novel use of a common sensory configuration, constituted by a force/torque sensor mounted between the tool and the flange of a robotic arm. The robotic...
Grasp planning in multi-robot systems is usually studied in a centralized setting with all robots sharing common knowledge about the overall system. Relaxing this assumption would allow multiple mobile manipulators to cooperate even without strict and precise coordination. Moreover, most typical tasks for cooperative settings, such as transporting heavy objects, require certain forces/torques to be...
This paper presents a physical human-robot interaction (pHRI) interface, which enables the user to control a walking humanoid robot through physical contact. A human operator guides the robot in parent-child-like behavior by exerting force onto the hand of the robot. In contrast to a conventional approach of pHRI in which force/torque measurements are applied, the proposed solution is based on sensorless...
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