Natural Landmark Detection of Mobile Robots Based on Bayesian Surprise of Salient Scenes
QIAN Kun,MA Xu-Dong,DAI Xian-Zhong,FANG Fang,YANG Hong
Key Laboratory of Measurement and Control of Complex Systems of Engineering of Ministry of Education,School of Automation,Southeast University,Nanjing 210096
Abstract：Nature landmark detection of mobile robot in unknown and unstructured environment is a basis of hierarchical environmental mapping. A natural landmark detection method is proposed based on Bayesian Surprise of salient scenes. Visual attention map of scene images is computed to guide the SURF feature sampling within the scope of salient regions. The improved spatial bag-of-words model (sBoW) is employed to construct the pattern vectors of scene appearance. Multivariate Polya model based on the spatial bag-of-words paradigm is proposed for representing the place,and the detection of landmarks corresponding to salient scenes is achieved by computing the surprise of sensor measurements. The experimental results validate the low miss alarm rate and false alarm rate of the nature landmark detection method in large-scale and complex environment,as well as the effectiveness of generating topological nodes with the combination of hierarchical SLAM method.
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2013, Vol. 26 
