Improving the Efficiency of Clearing with Multi-agent Teams

Hollinger, Geoffrey A.; Singh, Sanjiv; Kehagias, Athanasios

doi:10.1177/0278364910369949

Cited by 21 publications

(25 citation statements)

References 22 publications

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“…Finally, we refer the reader interested in more practical aspects of connected graph searching (including distributed computations) to works on algorithms and applications in the field of robotics [29,30,33,34,41].…”

Section: Related Workmentioning

confidence: 99%

Distributed graph searching with a sense of direction

2014

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In this work we consider the edge searching problem for vertex-weighted graphs with arbitrarily fast and invisible fugitive. The weight function ω provides for each vertex v the minimum number of searchers required to guard v, i.e., the fugitive may not pass through v without being detected only if at least ω(v) searchers are present at v. This problem is a generalization of the classical edge searching problem, in which one has ω ≡ 1. We assume that with a graph G to be searched, there is associated a partition (V 1 , . . . , V t ) of its vertex set such that edges are allowed only within each V i and between two consecutive V i 's. We provide an algorithm for distributed monotone connected edge searching of such graphs, where the searchers are initially placed on an arbitrary vertex of G and have no a priori knowledge on G, but they have a sense of direction that lets them recognize whether an edge incident to already explored vertex in V i leads to a vertex in one of V i−1 , V i or V i+1 . Starting from any vertex the algorithm uses at most 3·max i=1,...,t ω(V i )+1 searchers, where ω(V i ) = v∈V i ω(v). We also prove that this algorithm is best possible up to a small additive constant, that is, each distributed searching algorithm in worst case must use 3 · max i=1,...,t ω(V i ) − 1 searchers for some graphs.

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Section: Related Workmentioning

confidence: 99%

Distributed graph searching with a sense of direction

2014

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“…They provided a summary of the known complexity results for the minimum pursuer, minimum distance, and minimum time problems of various types of graphs. Hollinger et al (2010b) also examined the problem of minimizing distance using a heuristic that bootstraps on solutions to the adversarial search problem on an underlying spanning tree. Despite these recent efforts, we are left with the following open problems: A number of minimum time and minimum distance problems remain open on discrete graphs (see Table 1).…”

Section: Searching Environments Represented As Graphsmentioning

confidence: 99%

Search and pursuit-evasion in mobile robotics

2011

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This paper surveys recent results in pursuitevasion and autonomous search relevant to applications in mobile robotics. We provide a taxonomy of search problems that highlights the differences resulting from varying assumptions on the searchers, targets, and the environment. We then list a number of fundamental results in the areas of pursuit-evasion and probabilistic search, and we discuss field implementations on mobile robotic systems. In addition, we highlight current open problems in the area and explore avenues for future work.

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“…Then, in lines 09-15 we compute, for all legal extensions x = x&v (where v ∈ N [x t ]) of length t + 1 (line 10), the corresponding p (line 11) and C (by the subroutine Cost at line 12). We store these quantities in S which is placed in the temporary storage set S (lines [13][14]. After exhausting all possible extensions of length t + 1, we prune the temporary set S, retaining only the J max best cop sequences (this is done in line 17 by the subroutine Prune which computes "best" in terms of smallest C (x)).…”

Section: Algorithm For Drunk Robbermentioning

confidence: 99%

The Role of Visibility in Pursuit/Evasion Games

2014

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Abstract:The cops-and-robber (CR) game has been used in mobile robotics as a discretized model (played on a graph G) of pursuit/evasion problems. The "classic" CR version is a perfect information game: the cops' (pursuer's) location is always known to the robber (evader) and vice versa. Many variants of the classic game can be defined: the robber can be invisible and also the robber can be either adversarial (tries to avoid capture) or drunk (performs a random walk). Furthermore, the cops and robber can reside in either nodes or edges of G. Several of these variants are relevant as models or robotic pursuit/evasion. In this paper, we first define carefully several of the variants mentioned above and related quantities such as the cop number and the capture time. Then we introduce and study the cost of visibility (COV), a quantitative measure of the increase in difficulty (from the cops' point of view) when the robber is invisible. In addition to our theoretical results, we present algorithms which can be used to compute capture times and COV of graphs which are analytically intractable. Finally, we present the results of applying these algorithms to the numerical computation of COV.

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Improving the Efficiency of Clearing with Multi-agent Teams

Cited by 21 publications

References 22 publications

Distributed graph searching with a sense of direction

Distributed graph searching with a sense of direction

Search and pursuit-evasion in mobile robotics

The Role of Visibility in Pursuit/Evasion Games

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