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Cramer-Rao Lower Bound Analysis for Mobile Robot Navigation

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3 Author(s)
Zhimin Jiang ; School of Electrical and Electronic Engineering, BLK S2, Nanyang Technological University, Singapore 639798, Email: g00131892@ntu.edu.sg ; Sen Zhang ; Lihua Xie

This paper studies the Cramer-Rao Lower Bound (CRLB) of the simultaneous localization and map building (SLAM) problem for mobile robot navigation. Performance evaluation of SLAM is carried out and the Extended Kalman filtering (EKF) technique is verifed to be effective for the SLAM problem through the CRLB analysis. Detailed simulation and experimental results show that the process noise, measurement noise and feature number has influences on the CRLB of the SLAM.

Published in:

Intelligent Sensors, Sensor Networks and Information Processing Conference, 2005. Proceedings of the 2005 International Conference on

Date of Conference:

5-8 Dec. 2005