An omnidirectional camera simulation for the USARSim world

Omnidirectional vision is currently an important sensor in robotic research. The catadioptric omnidirectional camera with a hyperbolic convex mirror is a common omnidirectional vision system in the robotics research field as it has many advantages over other vision systems. This paper describes the development and validation of such a system for the RoboCup Rescue League simulator USARSim.
After an introduction of the mathematical properties of a real catadioptric omnidirectional camera we give a general overview of the simulation method. We then compare different 3D mirror meshes with respect to quality and system performance. Simulation data also is compared to real omnidirectional vision data obtained on an 4-Legged League soccer field. Comparison is based on using color histogram landmark detection and robot self-localization based on an Extended Kalman filter.