Abstract
Robots which are supposed to replace a human worker need sophisticated manipulation capabilities. Such capabilities are required for demanding everyday tasks as well as for specialized operations. This includes, e.g., dexterous manipulations in robot-assisted minimally invasive surgery. Sophisticated manipulation tasks require not only appropriate physical capabilities from the hardware, but also advanced knowledge about the dexterous manipulation task itself. Hence, we propose an abstract representation of dexterous manipulation knowledge. It is based on a contact state perspective of the environment. Objects in the environment are described relative to their specific type of contact with the environment. This enables a robot-independent reuse and adaption. The task can even be processed if the environment changes (e.g., due to occurrence of obstacles) of if another robot has to be used. Our experiments illustrate the flexibility which the representation provides. Obstacle avoidance and efficiency of the manipulator's motion are taken into account in the scenarios.
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