Stochastic volatility modeling with computational intelligence particle filters
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Ant Colony Estimator: An intelligent particle filter based on ACOR
Engineering Applications of Artificial Intelligence
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Robust simultaneous localization and map building (SLAM) is a key issue for mobile robot in presence of faults. In the paper, an adaptive evolutionary particle filter is designed to achieve robust SLAM for wheeled mobile robot when the laser range finder is subjected to errors. Firstly, a robust perception model for laser range finder is presented. The robustness of the provided model is two folds, (1) error beams of laser range finder are filtered out with segment analysis method, and (2) beams occluded by dynamical objects are filtered out with a high pass filter. Secondly, an adaptive mutation scheme is adopted to recover the diversity of the particles after resampling stage. Lastly, the presented method is testified in a real mobile robot.