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Body models in humans, animals, and robots
Humans and animals excel in combining information from multiple sensory ...
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Developing Embodied Multisensory Dialogue Agents
A few decades of work in the AI field have focused efforts on developing...
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Compact Real-time avoidance on a Humanoid Robot for Human-robot Interaction
With robots leaving factories and entering less controlled domains, poss...
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Variable impedance control and learning – A review
Robots that physically interact with their surroundings, in order to acc...
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Enabling the Sense of Self in a Dual-Arm Robot
While humans are aware of their body and capabilities, robots are not. T...
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The homunculus for proprioception: Toward learning the representation of a humanoid robot's joint space using self-organizing maps
In primate brains, tactile and proprioceptive inputs are relayed to the ...
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Diversity-based Design Assist for Large Legged Robots
We combine MAP-Elites and highly parallelisable simulation to explore th...
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Sensorimotor representation learning for an "active self" in robots: A model survey
Safe human-robot interactions require robots to be able to learn how to behave appropriately in humans' world spaces populated by people and thus to cope with the challenges posed by our dynamic and unstructured environment, rather than being provided a rigid set of rules for operations. In humans, these capabilities are thought to be related to our ability to perceive our body in space, sensing the location of our limbs during movement, being aware of other objects and agents, and controlling our body parts to interact with them intentionally. Toward the next generation of robots with bio-inspired capacities, in this paper, we first review the developmental processes of underlying mechanisms of these abilities: The sensory representations of body schema, peripersonal space, and the active self in humans. Second, we provide a survey of robotics models of these sensory representations and robotics models of the self; and we compare these models with the human counterparts. Finally, we analyse what is missing from these robotics models and propose a theoretical computational framework, which aims to allow the emergence of the sense of self in artificial agents by developing sensory representations through self-exploration.
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