This paper deals with a navigation of a mobile robot in a campus environment using a hand-drawn line drawing building map. Hand-drawn maps often include various types of uncertainty such as incorrect size/position and missing objects, thereby making it difficult to establish correspondence between objects in the map and sensory data. We solve this problem using a SLAM approach with an input hand-drawn map being an initial estimate. The proposed method combines a FastSLAM with a particle swarm optimization for map refinement. The method has been successfully applied to a stereo-based localization in a real scene.

No abstract

No abstract