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论文类型：期刊论文

发表时间：2013-02-01

发表刊物：IEEE International Symposium on Robotic and Sensors Environments (ROSE)

收录刊物：SCIE、EI、CPCI-S、Scopus

卷号：62

期号：2

页面范围：438-450

ISSN号：0018-9456

关键字：Autonomous place recognition; bearing-angle image; Speeded-Up Robust Features (SURFs); 3-D laser scanning; 3-D-laser-based scene measurement

摘要：Active environment perception and autonomous place recognition play a key role for mobile robots to operate within a cluttered indoor environment with dynamic changes. This paper presents a 3-D-laser-based scene measurement technique and a novel place recognition method to deal with the random disturbances caused by unexpected movements of people and other objects. The proposed approach can extract and match the Speeded-Up Robust Features (SURFs) from bearing-angle images generated by a self-built rotating 3-D laser scanner. It can cope with the irregular disturbance of moving objects and the problem of observing-location changes of the laser scanner. Both global metric information and local SURF features are extracted from 3-D laser point clouds and 2-D bearing-angle images, respectively. A large-scale indoor environment with over 1600 m(2) and 30 offices is selected as a testing site, and a mobile robot, i.e., SmartROB2, is deployed for conducting experiments. Experimental results show that the proposed 3-D-laser-based scene measurement technique and place recognition approach are effective and provide robust performance of place recognition in a dynamic indoor environment.