Robust self-localization of mobile robots using artificial and natural landmarks

This paper presents a novel localization paradigm for mobile robots based on artificial and natural landmarks. A model-based object recognition method detects natural landmarks and conducts the global and topological localization. In addition, a metric localization method using artificial landmarks...

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Bibliographic Details
Main Authors: Gijeong Jang, Sungho Kim, Wangheon Lee, Inso Kweon
Format: Conference Proceeding
Language:English
Subjects:
Computer science
Dead reckoning
Indoor environments
Mobile robots
Navigation
Object detection
Object recognition
Robustness
Voting
Wheels
Online Access:Request full text
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Summary:This paper presents a novel localization paradigm for mobile robots based on artificial and natural landmarks. A model-based object recognition method detects natural landmarks and conducts the global and topological localization. In addition, a metric localization method using artificial landmarks is fused to complement the deficiency of topology map and guide to action behavior. The recognition algorithm uses a modified local Zernike moments and a probabilistic voting method for the robust detection of objects in cluttered indoor environments. An artificial landmark is designed to have a three-dimensional multi-colored structure and the projection distortion of the structure encodes the distance and viewing direction of the robot. We demonstrate the feasibility of the proposed system through real world experiments using a mobile robot KASIRI-III.
DOI:10.1109/CIRA.2003.1222125