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Interaction of a robot with dynamic environments would require continuous adaptation of force and impedance, which is generally not available in current robot systems. In contrast, humans learn novel task dynamics with appropriate force and impedance through the concurrent minimization of error and energy, and exhibit the ability to modify movement trajectory to comply with obstacles and minimize...
This paper introduces a new approach to develop robots that can learn general affordance relations from their experiences. Our approach is a part of larger efforts to develop a cognitive robot and has two components: (a) the robot models affordances as statistical relations among actions, object properties and the effects of actions on objects, in the context of a goal that specifies preferred effects...
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