Localization of a wireless sensor network with
unattended ground sensors and some mobile robots.
Koushil Sreenath, Frank L. Lewis, and
Dan O. Popa. In IEEE International
Conference on Robotics, Automation, and Mechatronics (RAM), pages
1–8, Bangkok, Thailand, December 2006.
This paper won the IEEE RAM Conf. Best Paper Award
2006.
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Abstract
A range-free approach for adaptive localization of un-localized sensor nodes employing a mobile robot with GPS is detailed. A mobile robot navigates through the sensor deployment area broadcasting its positional estimate and the uncertainty in its estimate. Distributed computationallyinexpensive, discrete-time Kalman Filters, implemented on each static sensor node, fuse information obtained over time from the robot to decrease the uncertainty in each node’s location estimate. On the other hand, due to dead reckoning and other systematic errors, the robot loses positional accuracy over time. Updates from GPS and from the localized sensor nodes serve in improving the localization uncertainty of the robot. A Continuous-Discrete Extended Kalman Filter (CD EKF) running on the mobile robot fuses information from multiple distinct sources (GPS, various sensors nodes) for robot navigation. This two-part procedure achieves simultaneous localization of the sensor nodes and the mobile robot.Text Reference
Koushil Sreenath, Frank L. Lewis, and
Dan O. Popa,
"Localization of a wireless sensor network
with unattended ground sensors and some mobile robots",
In IEEE International Conference on Robotics, Automation, and Mechatronics
(RAM), pages 1–8, Bangkok, Thailand, December 2006,
This paper won the IEEE RAM Conf. Best Paper Award 2006.
BibTeX Reference
@conference{RAM2006,author = {Sreenath, Koushil and Lewis, Frank L. and Popa,
Dan O.},
title = {Localization of a Wireless Sensor Network with
Unattended Ground Sensors and Some Mobile Robots},
booktitle = {IEEE International Conference on Robotics,
Automation, and Mechatronics (RAM)},
pages = {1-8},
month = dec,
year = {2006},
address = {Bangkok, Thailand},
note = {This paper won the IEEE RAM Conf. Best Paper
Award 2006},
}