Application of traversability maps in the Virtual Rescue competition

This paper describes an exploration behavior which has been designed to explore large indoor areas. While exploring, traversability information is saved onto a layer in the map. This information is used in an A* algorithm has been implemented and is used for path planning. This approach allows the robot to learn from its experience and to find in the long run the "ideal line" to driving through the indoor environment

Amsterdam Oxford Joint Rescue Forces: Team description paper: Virtual Robot competition: Rescue Simulation League: RoboCup 2009

With the progress made in active exploration, the robots of the Joint Rescue Forces are capable of making deliberative decisions about the distributing exploration locations over the team. To navigate autonomously towards those locations, the robots gradually aggregate their experience in a traversability map. This traversability map can be used as basis to calculate an optimal path towards a goal. Robots equipped with both camera and laser-range scanners can learn a visual classifier of free space, which could be used by robots without laser-range scanners to navigate through the environment. Part of our algorithms have been validated on the Nomad Super Scout II robot available in our laboratory