Mobile Robot Localization Using Biased Chirp Spread Spectrum Ranging
SCIE
SCOPUS
- Title
- Mobile Robot Localization Using Biased Chirp Spread Spectrum Ranging
- Authors
- Cho, H; Kim, SW
- Date Issued
- 2010-08
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Abstract
- In this paper, we propose a method of mobile robot localization based on chirp-spread-spectrum (CSS) ranging. By using the CSS system, the distances between a mobile robot and CSS nodes fixed at known coordinates can be measured according to the time of flight of radio frequency signals. Based on the measured distances, the coordinates of a mobile robot can be calculated by the method of trilateration. To deal with measurement noise, an extended Kalman filter (EKF) can be applied to estimate the coordinate of the mobile robot. These measured distances, however, are not only noisy but also biased. Therefore, the estimated coordinates of the mobile robot represent inconsistent values. To solve the problem of bias, we define a scaling factor, which corresponds to the change of the magnitude of a measured distance vector that is due to biases. Based on the scaling factor, we develop a new biased measurement model and apply the EKF to our model for estimating the coordinates of a mobile robot. Through localization experiments, we evaluate the performance of the proposed algorithm.
- Keywords
- Chirp-spread-spectrum (CSS) ranging; extended Kalman filter (EKF); IEEE 802.15.4a; measurement bias; mobile robot localization; TRILATERATION
- URI
- https://oasis.postech.ac.kr/handle/2014.oak/27696
- DOI
- 10.1109/TIE.2009.2036633
- ISSN
- 0278-0046
- Article Type
- Article
- Citation
- IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, vol. 57, no. 8, page. 2826 - 2835, 2010-08
- Files in This Item:
- There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.