Abstract To meet the requirement of the indoor travelling and the localization of mobile robot, an approach for autonomous exploration, localization and mapping is proposed based on visual FastSLAM. Firstly, exploration position based on frontiers of the explored region is selected with consideration of information gain and path distance, and then path planning with the shortest distance to exploration position is performed to ensure the maximized exploration efficiency and completeness of the task accomplishment. FastSLAM 2.0 is employed as the basis of the proposed localization and mapping algorithm obtaining observation data by using robot vision, data observation efficiency is increased by fusing panoramic scanning and landmark tracking, and data association estimation is improved by introducing landmark visual information into calculation. The experimental results show that the proposed approach selects the best exploration position accurately, makes path planning reasonably, and accomplishes the exploration task successfully. The localization and mapping results of the proposed algorithm are robust with high accuracy.
Fund:Supported by National Natural Science Foundation of China(No.61403116,61271121), China Postdoctoral Science Foundation(No.2014M560507), Fundamental Research Funds for the Central Universities(No.2013HGBH0045)
About author:: (GAO Jun, born in 1963, Ph.D., professor. His research interests include intelligent information processing and pattern re-cognition.)(ZHANG Jun (Corresponding author), born in 1984, Ph.D., lecturer. Her research interests include computer vision, pattern recognition and cognitive science.)(FAN Zhiguo, born in 1978, Ph.D., associate professor. His research interests include information acquisition and proce-ssing, navigation and localization, target detection technology.)
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2016, Vol. 29 
