Improvement of the space observation model for robust mobile robot loclaization with unknown obstacles


This paper describes a localization technique for a mobile robot with unknown obstacles, such as pedestrians. Many robust localization technnique with unknown obstacles by using a particle filter and laser scanner have been propsed. In particular, Tomizawa’s method(Space observation model) is effective. However, this method has problem that it does not consider the fixed object occlusion. Thus, in the environment where thin wall (this is example), the robot position cannot be localized well. In this research, we solve this problem by rebulding the space information which is observed intrinsically in predicted position by considerinmg the fixed object occlusion. From above, we realize robot position localization with more high accuracy than previous method, by solving the problem of previous method and improving the previous method. We evaluate the validity of the proposed method by a simulation and an experiment in a real environment.

IECON 2013 - 39th Annual Conference of the IEEE Industrial Electronics Society