Abstract
Localization has been recognized as one of the most fundamental problem to provide a mobile robot with autonomous capabilities. This paper presents an Interval Constraint Satisfaction Problem (ICSP) based methodology for outdoor car-like robot localization. A bounded-error parameterization model for natural landmark is established. The localization problem is divided into two stages: visual teach and repeat. During a teaching stage, the interval map is built when robot navigates around the environment with GPS-support. The map is then used for ego-localization as the robot repeats the path autonomously. Different from probability filtering based methods, we cast the estimation problem into ICSP and use consistent and systematic searching techniques to retrieve all feasible solutions, leading to a guaranteed localization result. Experimental results show the soundness of the proposed method in achieving consistent localization.
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