NDLI: Probabilistic Localization of Service Robot by Sensor Fusion

Content Provider	IEEE Xplore Digital Library
Author	Hyeyeon Chang JongSuk Choi Munsang Kim
Copyright Year	2006
Description	Author affiliation: Intelligent Robotics Res. Center, Korea Adv. Inst. of Sci. & Technol., Seoul (Hyeyeon Chang)
Abstract	In recently years, various localization methods using two or more sensors have been proposed. Though it is still difficult to cope with the situation that the sensor data are polluted. In this paper, we proposed a probabilistic localization of service robot using laser scanner and indoor GPS system for treating sensor polluted situations. This scheme is a sample based algorithm as an application of Monte Carlo localization. In prediction phase, a number of samples are scattered by referring to the odometry data and position data of indoor GPS system. And those are evaluated by map-matching method using laser sensor and distance-error-matching using indoor GPS system in update phase. We are able to get more robust localization results by using these processes, even though the floor condition is deteriorated and there are many or huge obstacles. And it is possible to cope with severe errors which are caused when the robot is blocked by unexpected obstacles for a long time. However, adding another sensor and manipulating its data makes the computational consumption become larger. For overcoming these shorts, we had improved sensor model. Experimental results demonstrate the evaluation of the robustness of our algorithm fusing range image sensor and indoor GPS system data
Starting Page	3626
Ending Page	3631
File Size	6980140
Page Count	6
File Format	PDF
ISBN	8995003847
DOI	10.1109/SICE.2006.314892
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-10-18
Publisher Place	South Korea
Access Restriction	Subscribed
Rights Holder	The Institute of Control, Automation and Systems
Subject Keyword	Service robots Sensor fusion Global Positioning System Pollution Sensor systems Robustness Laser fusion Monte Carlo methods Scattering Robot sensing systems Range image sensor Monte Carlo localization Service Robot Indoor GPS system
Content Type	Text
Resource Type	Article

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