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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ho, C. Mora, A. Saripalli, S. |
| Copyright Year | 2012 |
| Description | Author affiliation: School of Earth and Space Exploration, Arizona State University, Tempe, 85284 USA (Ho, C.; Mora, A.; Saripalli, S.) |
| Abstract | A critical problem in planning sampling paths for autonomous underwater vehicles is balancing obtaining an accurate scalar field estimation against efficiently utilizing the stored energy capacity of the sampling vehicle. Adaptive sampling approaches can only provide solutions when real-time and a priori environmental data is available. Through utilizing a cost-evaluation function to experimentally evaluate various sampling path strategies for a wide range of scalar fields and sampling densities, it is found that a systematic spiral sampling path strategy is optimal for high-variance scalar fields for all sampling densities and low-variance scalar fields when sampling is sparse. The random spiral sampling path strategy is found to be optimal for low-variance scalar fields when sampling is dense. |
| Starting Page | 5328 |
| Ending Page | 5333 |
| File Size | 1639543 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781467314039 |
| ISSN | 10504729 |
| e-ISBN | 9781467314053 |
| e-ISBN | 9781467314046 |
| DOI | 10.1109/ICRA.2012.6225231 |
| 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 | Energy consumption Systematics Mathematical model Spirals Estimation Equations Vehicles |
| Content Type | Text |
| Resource Type | Article |
| Subject | Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software |
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