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This paper presents a new framework for mobile robot to perform localization and build topological-metric hybrid map simultaneously. The proposed framework termed as Genetic Bayesian ARAM consists of two main components: 1) Steady state genetic algorithm (SSGA) for self-localization and occupancy grid map building and 2) Bayesian Adaptive Resonance Associative Memory (ARAM) for topological map building...
Recently, robust estimators are expected in various fields such as signal processing and machine learning. In our previous work, we proposed Evolution Strategy Sample Consensus (ESSAC) as a new robust estimator method and improved a trade off between a calculation time and stability of SAmple Consensus (SAC) algorithms. In this paper, we show several experiments for behavior analysis of ESSAC in order...
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