Underwater Data Collection Using Robotic Sensor Networks
We examine the problem of utilizing an autonomous underwater vehicle (AUV) to collect data from an underwater sensor network. The sensors in the network are equipped with acoustic modems that provide noisy, range-limited communication. The AUV must plan a path that maximizes the information collecte...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | en_US |
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Institute of Electrical and Electronics Engineers (IEEE)
2014
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| Online Access: | http://hdl.handle.net/1721.1/87723 https://orcid.org/0000-0002-2621-7633 |
| _version_ | 1826200279144464384 |
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| author | Hollinger, Geoffrey A. Choudhary, Sunav Qarabaqi, Parastoo Murphy, Christopher Mitra, Urbashi Sukhatme, Gaurav S. Stojanovic, Milica Singh, Hanumant Hover, Franz S. |
| author2 | Massachusetts Institute of Technology. Department of Mechanical Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Mechanical Engineering Hollinger, Geoffrey A. Choudhary, Sunav Qarabaqi, Parastoo Murphy, Christopher Mitra, Urbashi Sukhatme, Gaurav S. Stojanovic, Milica Singh, Hanumant Hover, Franz S. |
| author_sort | Hollinger, Geoffrey A. |
| collection | MIT |
| description | We examine the problem of utilizing an autonomous underwater vehicle (AUV) to collect data from an underwater sensor network. The sensors in the network are equipped with acoustic modems that provide noisy, range-limited communication. The AUV must plan a path that maximizes the information collected while minimizing travel time or fuel expenditure. We propose AUV path planning methods that extend algorithms for variants of the Traveling Salesperson Problem (TSP). While executing a path, the AUV can improve performance by communicating with multiple nodes in the network at once. Such multi-node communication requires a scheduling protocol that is robust to channel variations and interference. To this end, we examine two multiple access protocols for the underwater data collection scenario, one based on deterministic access and another based on random access. We compare the proposed algorithms to baseline strategies through simulated experiments that utilize models derived from experimental test data. Our results demonstrate that properly designed communication models and scheduling protocols are essential for choosing the appropriate path planning algorithms for data collection. |
| first_indexed | 2024-09-23T11:34:02Z |
| format | Article |
| id | mit-1721.1/87723 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T11:34:02Z |
| publishDate | 2014 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | mit-1721.1/877232022-10-01T04:29:08Z Underwater Data Collection Using Robotic Sensor Networks Hollinger, Geoffrey A. Choudhary, Sunav Qarabaqi, Parastoo Murphy, Christopher Mitra, Urbashi Sukhatme, Gaurav S. Stojanovic, Milica Singh, Hanumant Hover, Franz S. Massachusetts Institute of Technology. Department of Mechanical Engineering Hover, Franz S. Hover, Franz S. We examine the problem of utilizing an autonomous underwater vehicle (AUV) to collect data from an underwater sensor network. The sensors in the network are equipped with acoustic modems that provide noisy, range-limited communication. The AUV must plan a path that maximizes the information collected while minimizing travel time or fuel expenditure. We propose AUV path planning methods that extend algorithms for variants of the Traveling Salesperson Problem (TSP). While executing a path, the AUV can improve performance by communicating with multiple nodes in the network at once. Such multi-node communication requires a scheduling protocol that is robust to channel variations and interference. To this end, we examine two multiple access protocols for the underwater data collection scenario, one based on deterministic access and another based on random access. We compare the proposed algorithms to baseline strategies through simulated experiments that utilize models derived from experimental test data. Our results demonstrate that properly designed communication models and scheduling protocols are essential for choosing the appropriate path planning algorithms for data collection. United States. Office of Naval Research (ONR N00014-09-1-0700) United States. Office of Naval Research (ONR N00014-07-1-00738) National Science Foundation (U.S.) (NSF 0831728) National Science Foundation (U.S.) (NSF CCR-0120778) National Science Foundation (U.S.) (NSF CNS-1035866) 2014-06-10T18:44:52Z 2014-06-10T18:44:52Z 2012-06 2012-04 Article http://purl.org/eprint/type/JournalArticle 0733-8716 http://hdl.handle.net/1721.1/87723 Hollinger, Geoffrey A., Sunav Choudhary, Parastoo Qarabaqi, Christopher Murphy, Urbashi Mitra, Gaurav S. Sukhatme, Milica Stojanovic, Hanumant Singh, and Franz Hover. “Underwater Data Collection Using Robotic Sensor Networks.” IEEE Journal on Selected Areas in Communications 30, no. 5 (n.d.): 899–911. https://orcid.org/0000-0002-2621-7633 en_US http://dx.doi.org/10.1109/jsac.2012.120606 IEEE Journal on Selected Areas in Communications Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Institute of Electrical and Electronics Engineers (IEEE) Prof. Hover via Angie Locknar |
| spellingShingle | Hollinger, Geoffrey A. Choudhary, Sunav Qarabaqi, Parastoo Murphy, Christopher Mitra, Urbashi Sukhatme, Gaurav S. Stojanovic, Milica Singh, Hanumant Hover, Franz S. Underwater Data Collection Using Robotic Sensor Networks |
| title | Underwater Data Collection Using Robotic Sensor Networks |
| title_full | Underwater Data Collection Using Robotic Sensor Networks |
| title_fullStr | Underwater Data Collection Using Robotic Sensor Networks |
| title_full_unstemmed | Underwater Data Collection Using Robotic Sensor Networks |
| title_short | Underwater Data Collection Using Robotic Sensor Networks |
| title_sort | underwater data collection using robotic sensor networks |
| url | http://hdl.handle.net/1721.1/87723 https://orcid.org/0000-0002-2621-7633 |
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