Title :
Information Based Distributed Control for Biochemical Source Detection and Localization
Author :
P. Tzanos;M. Zefran;A. Nehorai
Author_Institution :
Department of Electrical and Computer Engineering, University of Illinois at Chicago, Chicago, IL 60607
fDate :
6/27/1905 12:00:00 AM
Abstract :
The paper proposes several improvements on the Direction of Gradient (DOG) algorithm proposed in [1] for detecting and localizing a biochemical source with moving sensors. In particular, we show that the DOG algorithm can be turned into a distributed control scheme for a mobile sensing network, and that the maximum likelihood estimation proposed in the original algorithm can be replaced with more computationally efficient numerical procedures. Simulations on a single sensor and on a group of mobile sensors are provided that show that the proposed modifications simplify the original algorithm and improve its performance.
Keywords :
"Distributed control","Biosensors","Maximum likelihood estimation","Vehicles","Robot sensing systems","Robot kinematics","Sensor phenomena and characterization","Chemical sensors","Sensor arrays","Mobile robots"
Conference_Titel :
Robotics and Automation, 2005. ICRA 2005. Proceedings of the 2005 IEEE International Conference on
Print_ISBN :
0-7803-8914-X
DOI :
10.1109/ROBOT.2005.1570806