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Embodiment and Manipulation Learning Process for a Humanoid Hand

dc.date.accessioned2004-10-20T20:27:54Z
dc.date.accessioned2018-11-24T10:22:56Z
dc.date.available2004-10-20T20:27:54Z
dc.date.available2018-11-24T10:22:56Z
dc.date.issued1995-05-01en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/7064
dc.identifier.urihttp://repository.aust.edu.ng/xmlui/handle/1721.1/7064
dc.description.abstractBabies are born with simple manipulation capabilities such as reflexes to perceived stimuli. Initial discoveries by babies are accidental until they become coordinated and curious enough to actively investigate their surroundings. This thesis explores the development of such primitive learning systems using an embodied light-weight hand with three fingers and a thumb. It is self-contained having four motors and 36 exteroceptor and proprioceptor sensors controlled by an on-palm microcontroller. Primitive manipulation is learned from sensory inputs using competitive learning, back-propagation algorithm and reinforcement learning strategies. This hand will be used for a humanoid being developed at the MIT Artificial Intelligence Laboratory.en_US
dc.format.extent9161027 bytes
dc.format.extent7404933 bytes
dc.language.isoen_US
dc.titleEmbodiment and Manipulation Learning Process for a Humanoid Handen_US


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