Optimal Planning and Sampling Predictions for Autonomous and Lagrangian Platforms and Sensors in the Northern Arabian Sea
Where, when, and what to sample, and how to optimally reach the sampling locations, are critical questions to be answered by autonomous and Lagrangian platforms and sensors. For a reproducible scientific sampling approach, answers should be quantitative and provided using fundamental principles. Thi...
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| Format: | Article |
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The Oceanography Society
2018
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| Online Access: | http://hdl.handle.net/1721.1/115420 https://orcid.org/0000-0002-1869-3883 https://orcid.org/0000-0001-7354-6141 https://orcid.org/0000-0003-3518-6901 https://orcid.org/0000-0002-5972-8878 https://orcid.org/0000-0001-6942-2963 https://orcid.org/0000-0003-1347-5067 |
| _version_ | 1826209993322397696 |
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| author | Shcherbina, Andrey Lee, Craig Gangopadhyay, Avijit Lermusiaux, Pierre Haley, Patrick Jana, Sudip Gupta, Abhinav Kulkarni, Chinmay Sameer Mirabito, Chris Ali, Wael Narayanan Subramani, Deepak Dutt, Arkopal Lin, Jing |
| author2 | Massachusetts Institute of Technology. Department of Mechanical Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Mechanical Engineering Shcherbina, Andrey Lee, Craig Gangopadhyay, Avijit Lermusiaux, Pierre Haley, Patrick Jana, Sudip Gupta, Abhinav Kulkarni, Chinmay Sameer Mirabito, Chris Ali, Wael Narayanan Subramani, Deepak Dutt, Arkopal Lin, Jing |
| author_sort | Shcherbina, Andrey |
| collection | MIT |
| description | Where, when, and what to sample, and how to optimally reach the sampling locations, are critical questions to be answered by autonomous and Lagrangian platforms and sensors. For a reproducible scientific sampling approach, answers should be quantitative and provided using fundamental principles. This article reviews concepts and recent progress toward this principled approach, focusing on reachability, path planning, and adaptive sampling, and presents results of a real-time forecasting and planning experiment completed during February–April 2017 for the Northern Arabian Sea Circulation-autonomous research program. The predictive skill, layered fields, and uncertainty estimates obtained using the MIT MSEAS multi-resolution ensemble ocean modeling system are first studied. With such inputs, deterministic and probabilistic three-dimensional reachability forecasts issued daily for gliders and floats are then showcased and validated. Finally, a Bayesian adaptive sampling framework is shown to forecast in real time the observations that are most informative for estimating classic ocean fields and also secondary variables such as Lagrangian coherent structures. |
| first_indexed | 2024-09-23T14:39:00Z |
| format | Article |
| id | mit-1721.1/115420 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T14:39:00Z |
| publishDate | 2018 |
| publisher | The Oceanography Society |
| record_format | dspace |
| spelling | mit-1721.1/1154202022-10-01T21:56:29Z Optimal Planning and Sampling Predictions for Autonomous and Lagrangian Platforms and Sensors in the Northern Arabian Sea Shcherbina, Andrey Lee, Craig Gangopadhyay, Avijit Lermusiaux, Pierre Haley, Patrick Jana, Sudip Gupta, Abhinav Kulkarni, Chinmay Sameer Mirabito, Chris Ali, Wael Narayanan Subramani, Deepak Dutt, Arkopal Lin, Jing Massachusetts Institute of Technology. Department of Mechanical Engineering Lermusiaux, Pierre Haley, Patrick Jana, Sudip Gupta, Abhinav Kulkarni, Chinmay Sameer Mirabito, Chris Ali, Wael Narayanan Subramani, Deepak Dutt, Arkopal Lin, Jing Where, when, and what to sample, and how to optimally reach the sampling locations, are critical questions to be answered by autonomous and Lagrangian platforms and sensors. For a reproducible scientific sampling approach, answers should be quantitative and provided using fundamental principles. This article reviews concepts and recent progress toward this principled approach, focusing on reachability, path planning, and adaptive sampling, and presents results of a real-time forecasting and planning experiment completed during February–April 2017 for the Northern Arabian Sea Circulation-autonomous research program. The predictive skill, layered fields, and uncertainty estimates obtained using the MIT MSEAS multi-resolution ensemble ocean modeling system are first studied. With such inputs, deterministic and probabilistic three-dimensional reachability forecasts issued daily for gliders and floats are then showcased and validated. Finally, a Bayesian adaptive sampling framework is shown to forecast in real time the observations that are most informative for estimating classic ocean fields and also secondary variables such as Lagrangian coherent structures. 2018-05-16T20:25:06Z 2018-05-16T20:25:06Z 2017-09 2018-05-04T17:30:00Z Article http://purl.org/eprint/type/JournalArticle 1042-8275 http://hdl.handle.net/1721.1/115420 Lermusiaux, Pierre et al. “Optimal Planning and Sampling Predictions for Autonomous and Lagrangian Platforms and Sensors in the Northern Arabian Sea.” Oceanography 30, 2 (June 2017): 172–185 https://orcid.org/0000-0002-1869-3883 https://orcid.org/0000-0001-7354-6141 https://orcid.org/0000-0003-3518-6901 https://orcid.org/0000-0002-5972-8878 https://orcid.org/0000-0001-6942-2963 https://orcid.org/0000-0003-1347-5067 http://dx.doi.org/10.5670/OCEANOG.2017.242 Oceanography Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf The Oceanography Society Oceanography Society |
| spellingShingle | Shcherbina, Andrey Lee, Craig Gangopadhyay, Avijit Lermusiaux, Pierre Haley, Patrick Jana, Sudip Gupta, Abhinav Kulkarni, Chinmay Sameer Mirabito, Chris Ali, Wael Narayanan Subramani, Deepak Dutt, Arkopal Lin, Jing Optimal Planning and Sampling Predictions for Autonomous and Lagrangian Platforms and Sensors in the Northern Arabian Sea |
| title | Optimal Planning and Sampling Predictions for Autonomous and Lagrangian Platforms and Sensors in the Northern Arabian Sea |
| title_full | Optimal Planning and Sampling Predictions for Autonomous and Lagrangian Platforms and Sensors in the Northern Arabian Sea |
| title_fullStr | Optimal Planning and Sampling Predictions for Autonomous and Lagrangian Platforms and Sensors in the Northern Arabian Sea |
| title_full_unstemmed | Optimal Planning and Sampling Predictions for Autonomous and Lagrangian Platforms and Sensors in the Northern Arabian Sea |
| title_short | Optimal Planning and Sampling Predictions for Autonomous and Lagrangian Platforms and Sensors in the Northern Arabian Sea |
| title_sort | optimal planning and sampling predictions for autonomous and lagrangian platforms and sensors in the northern arabian sea |
| url | http://hdl.handle.net/1721.1/115420 https://orcid.org/0000-0002-1869-3883 https://orcid.org/0000-0001-7354-6141 https://orcid.org/0000-0003-3518-6901 https://orcid.org/0000-0002-5972-8878 https://orcid.org/0000-0001-6942-2963 https://orcid.org/0000-0003-1347-5067 |
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