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Content Provider | IEEE Xplore Digital Library |
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Author | Deshpande, N. Grant, E. Henderson, T.C. |
Copyright Year | 2012 |
Description | Author affiliation: School of Computing, University of Utah, Salt Lake City, USA (Henderson, T.C.) || Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, USA (Deshpande, N.; Grant, E.) |
Abstract | This paper extends the novel research for event localization and target-directed navigation using a deployed wireless sensor network (WSN) [4]. The goal is to have an autonomous mobile robot (AMR) navigate to a target-location by: (i) producing an artificial magnitude distribution within the WSN-covered region, and (ii) having the AMR use the pseudo-gradient from the interpolated distribution in its neighborhood, as it moves towards the target location. Implicit surfaces are used to interpolate the artificial distribution. This scheme only uses the topology of the WSN and received signal strength (RSS) to estimate an efficient navigation path for the AMR. Here, the AMR does not require global coordinates for the region, as it relies on local, neighborhood information alone to navigate. The performance of the scheme is analyzed with hardware experiments and in simulation, using a variety of node-densities and with increasing levels of noise to ensure robustness. |
Starting Page | 457 |
Ending Page | 462 |
File Size | 248785 |
Page Count | 6 |
File Format | |
ISBN | 9781467314039 |
ISSN | 10504729 |
e-ISBN | 9781467314053 |
e-ISBN | 9781467314046 |
DOI | 10.1109/ICRA.2012.6224997 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2012-05-14 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Interpolation Training Navigation Wireless sensor networks Trajectory Noise Splines (mathematics) received signal strength Target-directed navigation pseudo-gradient spline-interpolated distribution |
Content Type | Text |
Resource Type | Article |
Subject | Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software |
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