Sensor Resetting Localization for Poorly Modelled Mobile Robots

We present a new localization algorithm called Sensor Resetting Localization which is an extension of Monte Carlo Localization. The algorithm adds sensor based resampling to Monte Carlo Localization when the robot is lost. The new algorithm is robust to modelling errors including unmodelled movements and systematic errors. The algorithm can be used in real time on systems with limited computational power. The algorithm has been used successfully on autonomous legged robots in the Sony legged league of the robotic soccer competition RoboCup '99. We present results from the real robots demonstrating the success of the algorithm and results from simulation comparing the algorithm to Monte Carlo Localization.

• Type: Conference
• Year: 2000
• Where: ICRA
• Authors: Scott Lenser, Manuela M. Veloso
• Keywords: Algorithm, Algorithm Adds Sensor, ICRA 2000, Monte Carlo Localization, Robotics