An Improved Sensor Model on Appearance Based SLAM
نویسندگان
چکیده
In our previous work on visual, appearance-based localization and mapping, we presented in [14] a novel SLAM approach to build visually labeled topological maps. The essential contribution of this work was an adaptive sensor model, which is estimated online, and a graph matching scheme to evaluate the likelihood of a given topological map. Both methods enable the combination of an appearance-based, visual localization and mapping concept with a Rao-Blackwellized Particle Filter (RBPF) as state estimator to a real-world suitable, online SLAM approach. In this paper we improve our algorithm by using a novel probability driven approximation of the local similarity function (the sensor model) to deal with dynamic changes of the appearance in the operation area. 2
منابع مشابه
Improvements for an Appearance-based SLAM-Approach for Large-scale Environments
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