Online Determination of the Potential Benefit of Path Adaptation in Undersea Search

Baylog, John G.; Wettergren, Thomas A.

doi:10.1109/joe.2013.2286899

Cited by 5 publications

(2 citation statements)

References 29 publications

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“…The authors developed a game-theoretic approach to maximize the information flow that occurs as a multi-agent collaborative search is conducted over a bounded region. To accomplish this, they leverage search channel formalism [53]-an information theoretic tool which models the information flow over small region (cells) of the search space. It allows the authors to compute the information measure of each cell as a function of searcher regional visitation.…”

Section: Coverage and Search Planning Gamesmentioning

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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Section: Coverage and Search Planning Gamesmentioning

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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“…Over a long time interval, the benefits of adaptive autonomous search are overcome by performance of standard preplanned search paths. 21 If the goal of the mission is to find an object as soon as possible (as in search and rescue operations), it would be advisable for the vehicle to react to new information for a small interval of time. However, if the goal is to find all the objects in the area over a fixed interval of time then it is more beneficial to to maintain its initially planned paths for the duration of the search.…”

Section: Introductionmentioning

confidence: 99%

Minehunting Mission Planning for Autonomous Underwater Systems Using Evolutionary Algorithms

Abreu

Matos

2014

Un. Sys.

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Autonomous underwater vehicles (AUVs) are increasingly being used to perform mine countermeasures (MCM) operations but its capabilities are limited by the efficiency of the planning process. Here we study the problem of multiobjective MCM mission planning with AUVs. The vehicle should cover the operating area while maximizing the probability of detecting the targets and minimizing the required energy and time to complete the mission. A multi-stage algorithm is proposed and evaluated. Our algorithm combines an evolutionary algorithm (EA) with a local search procedure, aiming at a more flexible and effective exploration and exploitation of the search space. An artificial neural network (ANN) model was also integrated in the evolutionary procedure to guide the search. The combination of different techniques creates another problem, related to the high amount of parameters that needs to be tuned. Thus, the effect of these parameters on the quality of the obtained Pareto Front was assessed. This allowed us to define an adaptive tuning procedure to control the parameters while the algorithm is executed. Our algorithm is compared against an implementation of a known EA as well as another mission planner and the results from the experiments show that the proposed strategy can efficiently identify a higher quality solution set.

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Persistent Schedule Evaluation and Adaptive Re-planning for Maritime Search Tasks

Bays,

Wettergren,

Shin

et al. 2024

J Intell Robot Syst

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Search operations performed by adaptive autonomous maritime vehicles have been a topic of considerable interest for many years. Such operations require carefully scheduled coordination of multiple vehicles performing search tasks across the region of interest. Due to the inherent uncertainty of the maritime environment, however, an initially planned search schedule may not be maintained if the vehicles have significant capability to adapt their tasks to match the environment they detect in real time. We propose a multi-vehicle adaptive algorithm for dynamic evaluation and elastic re-planning of variable-length tasks commonly found in the maritime environments. In adaptive evaluation and re-planning problems, a set of tasks are initially planned for execution by adaptive, autonomous search vehicles. Tasks are allocated to search vehicles under a pre-defined schedule based on prior knowledge and desired outcome. Because of the vehicles’ autonomy and reactivity to in situ conditions such as environment or target pose, the precise duration and actions required by each task are unknown a priori. We develop a hidden Markov model (HMM) for propagating task estimates, coupled with a quadratic-programming-based elastic re-scheduler. The result is an integrated estimate-and-schedule adaptation scheme that quickly and efficiently re-plans the vehicles’ schedules based on in situ observations. The numerical simulation results show that this novel HMM approach decreases avoidable schedule variation by over a factor of two compared to existing methods.

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Online Determination of the Potential Benefit of Path Adaptation in Undersea Search

Cited by 5 publications

References 29 publications

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

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

Minehunting Mission Planning for Autonomous Underwater Systems Using Evolutionary Algorithms

Persistent Schedule Evaluation and Adaptive Re-planning for Maritime Search Tasks

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