The role of exploration in learning has already been long a research item in our group and we plan to incorporate our knowledge of exploration in Reinforcement Learning in the project. Simulation and tests Developed methods are first tested in our robot simulator. This simulator is unique in the sense that it is very flexible in incorporating new sensor models or other autonomous robot agents. This database is provided by Tsukuba Research Center, Japan, for the Real World Computing Partnership and contains a dataset of about 8000 robot positions and associated measurements from sonars, infrared sensors and camera images. The robot is equipped with an omnidirectional vision system.
Processing is done on-board.
SMC'99, IEEE Int. Conf. on Systems, Man, and Cybernetics, Tokyo, Japan, Oct 1999. Heading direction for a Mobile Robot from Optic Flow ,'' Proceedings of the IEEE International Conference on Robotics and Automation, pp. Proceedings IROS'97, IEEE , pp.