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Efficient Human-like Dexterous Grasping under Uncertainty for Robotics

Imagine that you are reaching into the fridge to grasp an object you can only partially see. Rather than relying solely on vision, you must use touch in order to localise it and securely grasp it. However, humans would not poke the object to localise it first and then grasp it. We compensate for the uncertainty by approaching the object in a way such that if a contact occurs it will generate enough information about where the object is and the object will be grasped with a minimum adaptation of the initial trajectory.

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