Autonomy for surface ship interception

Mirabito, Chris; Subramani, Deepak N.; Lolla, Tapovan; Haley, Patrick J.; Jain, Ankita; Lermusiaux, Pierre F. J.; Li, C.; Yue, Dick K. P.; Liu, Y.; Hover, Franz S.; Pulsone, N.B.; Edwards, Joseph R.; Railey, Kristen; Shaw, Graeme B.

doi:10.1109/oceanse.2017.8084817

Cited by 9 publications

(9 citation statements)

References 36 publications

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“…Reachability and path panning with differential equations: Realistic planning and computational costs. The reachable sets, fronts, and optimal paths can be predicted, depending on applications, in 2D or 3D space (Kulkarni 2017), for isotropic and anisotropic motions (Lolla and Lermusiaux 2018), and for several types of ocean vehicles such as floats, gliders (Lolla et al 2014a,b;, propelled vehicles (Subramani et al 2017), and surface kayaks or ships in wave conditions (Mirabito et al 2017). Today, the computational time for all of these applications is much shorter than the mission time, even with a single CPU.…”

Section: A Reachability and Path Panningmentioning

confidence: 99%

A future for intelligent autonomous ocean observing systems

Lermusiaux¹,

Subramani²,

Lin³

et al. 2017

j mar res

Self Cite

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Ocean scientists have dreamed of and recently started to realize an ocean observing revolution with autonomous observing platforms and sensors. Critical questions to be answered by such autonomous systems are where, when, and what to sample for optimal information, and how to optimally reach the sampling locations. Definitions, concepts, and progress towards answering these questions using quantitative predictions and fundamental principles are presented. Results in reachability and path planning, adaptive sampling, machine learning, and teaming machines with scientists are overviewed. The integrated use of differential equations and theory from varied disciplines is emphasized. The results provide an inference engine and knowledge base for expert autonomous observing systems. They are showcased using a set of recent at-sea campaigns and realistic simulations. Real-time experiments with identical autonomous underwater vehicles (AUVs) in the Buzzards Bay and Vineyard Sound region first show that our predicted time-optimal paths were faster than shortest distance paths. Deterministic and probabilistic reachability and path forecasts issued and validated for gliders and floats in the northern Arabian Sea are then presented. Novel Bayesian adaptive sampling for hypothesis testing and optimal learning are finally shown to forecast the observations most informative to estimate the accuracy of model formulations, the values of ecosystem parameters and dynamic fields, and the presence of Lagrangian Coherent Structures.

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Section: A Reachability and Path Panningmentioning

confidence: 99%

A future for intelligent autonomous ocean observing systems

Lermusiaux¹,

Subramani²,

Lin³

et al. 2017

j mar res

Self Cite

View full text Add to dashboard Cite

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“…Additional areas of development for VISIR may include some problems already addressed through the LSE, such as interceptions and multi-waypoint missions [29], [55], [56], energy optimization [54], onboard learning [57], and clustering of vessels to low-risk routes in uncertain flow environments [67]- [69].…”

Section: Discussionmentioning

confidence: 99%

Graph-Search and Differential Equations for Time-Optimal Vessel Route Planning in Dynamic Ocean Waves

Mannarini

Subramani

Lermusiaux

et al. 2020

IEEE Trans. Intell. Transport. Syst.

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Time-optimal paths are evaluated by VISIR ("dis-coVerIng Safe and effIcient Routes"), a graph-search ship routing model, with respect to the solution of the fundamental differential equations governing optimal paths in a dynamic wind-wave environment. The evaluation exercise makes use of identical setups: topological constraints, dynamic wave environmental conditions, and vessel-ocean parametrizations, while advection by external currents is not considered. The emphasis is on predicting the time-optimal ship headings and Speeds Through Water constrained by dynamic ocean wave fields. VISIR upgrades regarding angular resolution, time-interpolation, and static navigational safety constraints are introduced. The deviations of the graph-search results relative to the solution of the exact differential equations in both the path duration and length are assessed. They are found to be of the order of the discretization errors, with VISIR's solution converging to that of the differential equation for sufficient resolution.

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“…In [33], the authors extend the previous work to the case of multiple pursuers. In [29], the authors validate the efficacy of the proposed methodology with testing in realistic data-assimilative simulated environments. A theoretical background and seminal studies on the use of this approach for path planning in marine environment can be found in [17,34,35].…”

Section: Pursuit-evasion Gamesmentioning

confidence: 91%

“…For instance, the solution to the minimum time navigation problem in dynamic flows is governed by a Hamilton-Jacobi-Bellman equation [28] (calculus of variations). Examples in path planning include the interception of ships [29].…”

Section: Path Planning Games In Marine Domainmentioning

confidence: 99%

Game Theory for Unmanned Vehicle Path Planning in the Marine Domain: State of the Art and New Possibilities

Cococcioni

Fiaschi

Lermusiaux

2021

JMSE

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Thanks to the advent of new technologies and higher real-time computational capabilities, the use of unmanned vehicles in the marine domain has received a significant boost in the last decade. Ocean and seabed sampling, missions in dangerous areas, and civilian security are only a few of the large number of applications which currently benefit from unmanned vehicles. One of the most actively studied topic is their full autonomy; i.e., the design of marine vehicles capable of pursuing a task while reacting to the changes of the environment without the intervention of humans, not even remotely. Environmental dynamicity may consist of variations of currents, the presence of unknown obstacles, and attacks from adversaries (e.g., pirates). To achieve autonomy in such highly dynamic uncertain conditions, many types of autonomous path planning problems need to be solved. There has thus been a commensurate number of approaches and methods to optimize this kind of path planning. This work focuses on game-theoretic approaches and provides a wide overview of the current state of the art, along with future directions.

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Autonomy for surface ship interception

Cited by 9 publications

References 36 publications

A future for intelligent autonomous ocean observing systems

A future for intelligent autonomous ocean observing systems

Graph-Search and Differential Equations for Time-Optimal Vessel Route Planning in Dynamic Ocean Waves

Game Theory for Unmanned Vehicle Path Planning in the Marine Domain: State of the Art and New Possibilities

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