Reinforcement Learning for Platform-Independent Visual Robot Control

David Muse , Kevin Burn , Stefan Wermter
International Joint Conference on Neural Networks, pages 2459--2466, doi: 10.1109/IJCNN.2006.247094 - Jan 2006
Associated documents :  
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.

 

@InProceedings{MBW06, 
 	 author =  {Muse, David and Burn, Kevin and Wermter, Stefan},  
 	 title = {Reinforcement Learning for Platform-Independent Visual Robot Control}, 
 	 booktitle = {International Joint Conference on Neural Networks},
 	 editors = {},
 	 number = {},
 	 volume = {},
 	 pages = {2459--2466},
 	 year = {2006},
 	 month = {Jan},
 	 publisher = {IEEE},
 	 doi = {10.1109/IJCNN.2006.247094}, 
 }