Perception through visuomotor anticipation in a mobile robot
Neural Networks
Gibsonian Affordances for Roboticists
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
To Afford or Not to Afford: A New Formalization of Affordances Toward Affordance-Based Robot Control
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Space Perception through Visuokinesthetic Prediction
Anticipatory Behavior in Adaptive Learning Systems
Interacting with Computers
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According to several authors in psychology and neurosciences, our ability to perceive affordances is subtended by motor simulation mechanisms. Such mechanisms provide dynamic representations of feasible actions, thus enabling to scale the surrounding structures on the behavioural repertoire and capacities supported by our body. This attractive hypothesis has been taken up in robotics, to build intelligent systems able to determine in advance whether a given action would be successful given the current state of the environment and their own skills. Several arguments, however, suggest that the motor simulation framework is not sufficient to explain affordance perception: (1) it rests on a misunderstanding of what affordances are: not actions that are currently feasible, but actions that are possible; (2) it is computationally unrealistic: motor simulation is too costly in terms of computational resources to explain how one can access prospectively to actions that are potentiated by surrounding structures; (3) it only covers the part of the perceptual field within the scope of our attention, but the affordances we perceive do not reduce to the object or state of affairs our attention is focused on at time t; and (4) it can only work if a first layer of affordances is available: motor simulation cannot explain affordance perception, because its very functioning presupposes such perception. Other mechanisms must consequently be hypothesized.