NDLI: Adaptive sampling for environmental field estimation using robotic sensors

Content Provider	IEEE Xplore Digital Library
Author	Rahimi, M. Hansen, M. Kaiser, W.J. Sukhatme, G.S. Estrin, D.
Copyright Year	2005
Description	Author affiliation: Center for Embedded Networked Sensing, UCLA, Los Angeles, CA, USA (Rahimi, M.; Hansen, M.; Kaiser, W.J.; Sukhatme, G.S.; Estrin, D.)
Abstract	Monitoring environmental phenomena by distributed sensor sampling confronts the challenge of unpredictable variability in the spatial distribution of phenomena often coupled with demands for a high spatial sampling rate. The introduction of actuation-enabled robotics sensors permits a system to optimize the sampling distribution through runtime adaptation. However, such systems must efficiently dispense sampling points or otherwise suffer from poor temporal response. In this paper, we propose and characterize an active modeling system. In our approach, as the robotic sensor acquires measurement samples of the environment, it builds a model of the phenomenon. Our algorithm is based on an incremental optimization process where the robot supports a continuous, iterative process of 1) collecting samples with maximal coverage in the design space; 2) building the environmental model; 3) predicting sampling point locations that contribute the greatest certainty regarding the phenomenon; and 4) sampling the environment based on a combined measure of information gain and navigation and sampling cost. This can provide significant reductions in the magnitude of field estimation error with a modest navigational trajectory time. We evaluate our algorithm through a simulation, using a combination of static and mobile sensors sampling light illumination field.
Starting Page	3692
Ending Page	3698
File Size	441186
Page Count	7
File Format	PDF
ISBN	0780389123
DOI	10.1109/IROS.2005.1545070
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-08-02
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sampling methods Robot sensing systems Sensor phenomena and characterization Orbital robotics Navigation Monitoring Sensor systems Runtime Iterative algorithms Design optimization Field Estimation Adaptive Sampling Modeling
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Area-constrained coverage optimization by robotic sensor networks

Robotic deployment for environmental sampling applications

Adaptive Sampling using Non-linear EKF with Mobile Robotic Wireless Sensor Nodes

EKF-based Adaptive Sampling with Mobile Robotic Sensor Nodes

Multiple sensor processing for high-precision navigation and environmental modeling with a mobile robot

A Non-Parametric Iterative Algorithm For Adaptive Sampling And Robotic Vehicle Path Planning

Multi-sensor integration for robotic assembly

Field-tests of a redundantly actuated cable-driven robot for environmental sampling applications

Optimization of waypoint-guided potential field navigation using evolutionary algorithms

Adaptive sampling for environmental field estimation using robotic sensors

Similar Documents

Area-constrained coverage optimization by robotic sensor networks

Robotic deployment for environmental sampling applications

Adaptive Sampling using Non-linear EKF with Mobile Robotic Wireless Sensor Nodes

EKF-based Adaptive Sampling with Mobile Robotic Sensor Nodes

Multiple sensor processing for high-precision navigation and environmental modeling with a mobile robot

A Non-Parametric Iterative Algorithm For Adaptive Sampling And Robotic Vehicle Path Planning

Multi-sensor integration for robotic assembly

Field-tests of a redundantly actuated cable-driven robot for environmental sampling applications

Optimization of waypoint-guided potential field navigation using evolutionary algorithms

Adaptive sampling for environmental field estimation using robotic sensors