DocumentCode :
442241
Title :
Robotic deployment for environmental sampling applications
Author :
Popa, Dan O. ; Sreenath, Koushil ; Lewis, Frank L.
Author_Institution :
Autom. & Robotics Res. Inst., Texas Univ., Arlington, TX, USA
Volume :
1
fYear :
2005
fDate :
26-29 June 2005
Firstpage :
197
Abstract :
The use of robotics in environmental monitoring applications requires distributed sensor systems optimized for effective estimation of relevant models subject to energy and environmental constraints. The sensor carrying robots are in fact agents that facilitate the repositioning of network nodes in order to increase their coverage and accuracy. Wireless or acoustic network communication is an essential technology in transmitting the sensed as well as telemetry information between robots. Each mobile sensing node (robot) is characterized by sensing or measurement noise, localization uncertainty, and navigates in a region with a parameterized field model. This paper addresses a problem of great importance to the SN robotic deployment: adaptive sampling by selection and repositioning of mobile sensing nodes in order to optimally estimate the parameters of distributed variable field models. We present simulation results using deployment scenarios that will be experimentally validated at a future date.
Keywords :
Kalman filters; distributed sensors; environmental factors; mobile robots; sampling methods; sensor fusion; telerobotics; uncertain systems; Kalman filter; adaptive sampling; distributed sensor systems; distributed variable field models; environmental monitoring; environmental sampling; localization uncertainty; measurement noise; mobile sensing node; navigation; network node repositioning; parameterized field model; robotic deployment; sensor carrying robots; telemetry information; Acoustic sensors; Constraint optimization; Mobile communication; Mobile robots; Monitoring; Robot sensing systems; Sampling methods; Sensor phenomena and characterization; Sensor systems; Wireless sensor networks; Adaptive Sampling; Environmental Sampling; Kalman Filter; Sensor Networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Automation, 2005. ICCA '05. International Conference on
Print_ISBN :
0-7803-9137-3
Type :
conf
DOI :
10.1109/ICCA.2005.1528116
Filename :
1528116
Link To Document :
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