Mobile Robot Self-localization Based on Feature Extraction of Laser Scanner Using Self-organizing Feature Mapping

Authors:
Jinxia Yu;Zixing Cai;Zhuohua Duan
Affiliations:
College of Computer Science & Technology, Henan Polytechnic University, Jiaozuo 454003, Henan, China and College of Information Science & Engineering, Central South University, Changsha 410083, Hu ...;College of Information Science & Engineering, Central South University, Changsha 410083, Hunan, China;College of Information Science & Engineering, Central South University, Changsha 410083, Hunan, China and Department of Computer Science, Shaoguan University, Shaoguan 512003, Guangdong, China
Venue:
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Advances in Neural Networks
Year:
2007

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Abstract

This paper investigates the use of SOM to process the signal of a 2D laser scanner encountered in feature extraction (corner) and mobile robot self-localization in indoor environments. It presents the method of combining SOM with occupancy grid matching to improve the self-localization performance at the lower computational cost. Experimental results demonstrate that this method can reliably extract the feature of corner point and can effectively improve the self-localization performance of mobile robot.