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| Map Building Method Based on Hierarchical Temporal Memory |
| ZHANG Xin-Zheng1, MAI Xiao-Chun2, ZHANG Jian-Fen1 |
1.Electrical and Information College, Jinan University, Zhuhai 519070
2.Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong 999077 |
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Abstract A map building method based on hierarchical temporal memory (HTM)is proposed. The mapping problem is treated as scene recognition. The map is composed of a series of scenes being the outputs of HTM network. Firstly, the position invariant robust feature (PIRF) is extracted from the obtained images and then the PIRFs are applied to build the visual vocabulary. Secondly, according to the visual vocabulary PIRF descriptors of an image are projected to the vector of visual word occurrences. Multiple visual word occurrences vectors are formed as a sequence of visual word occurrences. This sequence is inputted to HTM to implement the environment map learning and building and closed loop scenes recognition. The performance of the proposed mapping method is evaluated by two experiments. The results show that the proposed strategy based on HTM is effective for map building and closed loop detection.
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Received: 02 January 2014
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2015, Vol. 28 
