Search Path Evaluation Incorporating Object Placement Structure

Baylog, John G.; Wettergren, Thomas A.

doi:10.21236/ada475983

Cited by 4 publications

(7 citation statements)

References 5 publications

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“…where, following (11), the mutual information over the partition becomes (23) Theorem 1: Assume a search channel without false alarms. Then, the mutual information between object placement and a repeated look over a cell search channel is the same as that between placement and a first detection waiting time output.…”

Section: Search Channel Capacitymentioning

confidence: 99%

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

Baylog

Wettergren

2014

IEEE J. Oceanic Eng.

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In this paper, we examine a problem of autonomous vehicle decision making for search operations performed by undersea autonomous vehicles. Specifically, we consider the problem of determining whether to continue with preplanned search paths or to switch to focused local search efforts in the presence of limited contact information. Using techniques from information theory, we develop a context of search channel capacity from which rapid computations of performance bounds can be computed based on sensing capabilities and prior search information. These bounds characterize search planning alternatives and are useful in making the initial online determination of search plan adaptation. We illustrate the utility of our approach with numerical examples applying multiple undersea searchers.

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Section: Search Channel Capacitymentioning

confidence: 99%

“…In this paper, we build upon our previous work in coordinated search performance evaluation under the condition of geospatial variability [16], [23]. We develop a search capacity measure of performance analogous to the channel capacity developed for communication theory.…”

Section: Introductionmentioning

confidence: 99%

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

Baylog

Wettergren

2014

IEEE J. Oceanic Eng.

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“…The method of utility developed in this paper applies a cell referenced framework as in the case of the well defined search path [6]. Hence, navigational error imposes a calculation of cell visitation probabilities.…”

Section: B Event Space Definitionmentioning

confidence: 99%

“…When visitation is certain, the recursion of equation 46 becomes invariant prior to and after the cell passage (at values 0 and 1 respectively). When this happens, it reduces to the approach taken in [6] when ancillary dependency is not present.…”

Section: Equation 41 Separates Detection and Sensor Scan Visitation Withmentioning

confidence: 99%

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Robust modeling of navigation error for UUV mission planning

Baylog

Wettergren

2012

2012 Oceans

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In this paper we present an analytical model for incorporating navigational error into a search performance prediction algorithm through the construction of a corresponding utility function. The search space is partitioned into a set of cells over which a utility function formulation is developed for each. The navigational displacement error is assumed to be driven by a Mixed Ornstein Uhlenbeck stochastic process. The evaluation method is based upon our previous work on utility functions as perturbative forms on Bayesian recursion models for search effectiveness modeling with non-trivial dependencies. This paper presents the development of the cell-based probability recursions for the spatially correlated navigational error. From these, a sequential formulation for utility update is developed.

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Robust search for structured object placement using unmanned vehicles

Baylog¹,

Wettergren²,

Hyland³

et al. 2008

Oceans 2008

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We develop a robust method for planning an undersea search by unmanned vehicles; the goal of which is to find groups of objects that may be placed randomly or arranged in predefined patterns on the ocean floor. This approach revolves around the computation of target pattern priors that describe the underlying geometrical structure of the expected group of objects. These priors are updated based on limited search observations, followed by a search performance assessment in the remaining region utilizing these observed target pattern distributions. We outline the derivation of this approach to assessing the performance of unmanned searches. The algorithms performance is tested in a simulation example to illustrate the improvement in search evaluation accuracy provided by the consideration of object structure. We conclude with a discussion of how this search planning strategy can be employed in realistic scenarios, searching for objects that are expected to appear in more general patterns.

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Search Path Evaluation Incorporating Object Placement Structure

Abstract: REPORT DOCUMENTATION PAGE

Cited by 4 publications

References 5 publications

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

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

Robust modeling of navigation error for UUV mission planning

Robust search for structured object placement using unmanned vehicles

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