{"id":3969,"date":"2017-01-03T12:00:35","date_gmt":"2017-01-03T17:00:35","guid":{"rendered":"http:\/\/mseas.mit.edu\/?p=3969"},"modified":"2021-07-06T13:03:48","modified_gmt":"2021-07-06T17:03:48","slug":"energy-optimal-path-planning-in-the-coastal-ocean","status":"publish","type":"post","link":"https:\/\/mseas.mit.edu\/?p=3969","title":{"rendered":"Energy-optimal path planning in the coastal ocean"},"content":{"rendered":"We integrate data-driven ocean modeling with the stochastic Dynamically\r\nOrthogonal (DO) level-set optimization methodology to compute and study energy-optimal\r\npaths, speeds, and headings for ocean vehicles in the Middle-Atlantic Bight (MAB) region.\r\nWe hindcast the energy-optimal paths from among exact time-optimal paths for\r\nthe period 28 August 2006 to 9 September 2006. To do so, we first obtain a data-assimilative\r\nmultiscale re-analysis, combining ocean observations with implicit two-way nested multiresolution\r\nprimitive-equation simulations of the tidal-to-mesoscale dynamics in the region.\r\nSecond, we solve the reduced-order stochastic DO level-set partial differential equations\r\n(PDEs) to compute the joint probability of minimum arrival-time, vehicle-speed\r\ntime-series, and total energy utilized. Third, for each arrival time, we select the vehiclespeed\r\ntime-series that minimize the total energy utilization from the marginal probability\r\nof vehicle-speed and total energy. The corresponding energy-optimal path and headings\r\nare obtained through a particle backtracking equation. Theoretically, the present\r\nmethodology is PDE-based and provides fundamental energy-optimal predictions without\r\nheuristics. Computationally, it is three- to four-orders of magnitude faster than direct\r\nMonte Carlo methods. For the missions considered, we analyze the effects of the regional\r\ntidal currents, strong wind events, coastal jets, shelfbreak front, and other local\r\ncirculations on the energy-optimal paths. Results showcase the opportunities for vehicles\r\nthat intelligently utilize the ocean environment to minimize energy usage, rigorously\r\nintegrating ocean forecasting with optimal control of autonomous vehicles.","protected":false},"excerpt":{"rendered":"<p>We integrate data-driven ocean modeling with the stochastic Dynamically Orthogonal (DO) level-set optimization methodology to compute and study energy-optimal paths, speeds, and headings for ocean vehicles in the Middle-Atlantic Bight (MAB) region. We hindcast the energy-optimal paths from among exact time-optimal paths for the period 28 August 2006 to 9 September 2006. To do so, [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[183,35,5,63],"tags":[],"class_list":["post-3969","post","type-post","status-publish","format-standard","hentry","category-science-of-autonomy","category-optimal-path-planning","category-publications","category-papers-in-refereed-journals-optimal-path-planning"],"_links":{"self":[{"href":"https:\/\/mseas.mit.edu\/index.php?rest_route=\/wp\/v2\/posts\/3969","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/mseas.mit.edu\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/mseas.mit.edu\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/mseas.mit.edu\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/mseas.mit.edu\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=3969"}],"version-history":[{"count":5,"href":"https:\/\/mseas.mit.edu\/index.php?rest_route=\/wp\/v2\/posts\/3969\/revisions"}],"predecessor-version":[{"id":4232,"href":"https:\/\/mseas.mit.edu\/index.php?rest_route=\/wp\/v2\/posts\/3969\/revisions\/4232"}],"wp:attachment":[{"href":"https:\/\/mseas.mit.edu\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3969"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/mseas.mit.edu\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3969"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/mseas.mit.edu\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3969"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}