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18

IJCNN
2006
IEEE

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Reinforcement Learning for Platform-Independent Visual Robot Control

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Reinforcement Learning for Platform-Independent Visual Robot Control

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—This paper proposes a new architecture for robot control. A test scenario is outlined to test the proposed system and enable a comparison with an existing system, which is able to fulfil the scenario and thus be used as a benchmark. The scenario is a navigation task, to allow a robot to approach a specified landmark. The proposed architecture will make use of two control units, one to allow a pan/tilt camera to track the landmark as the robot moves, and a second to control the robots drive motors. These units will be trained via reinforcement learning, and provide the potential for platformindependent robot control.

David Muse, Kevin Burn, Stefan Wermter

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Added	11 Jun 2010
Updated	11 Jun 2010
Type	Conference
Year	2006
Where	IJCNN
Authors	David Muse, Kevin Burn, Stefan Wermter

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