# Visibility-Based Pursuit-Evasion in a Polygonal Environment

@inproceedings{Guibas1997VisibilityBasedPI, title={Visibility-Based Pursuit-Evasion in a Polygonal Environment}, author={Leonidas J. Guibas and Jean-Claude Latombe and Steven M. LaValle and David C. Lin and Rajeev Motwani}, booktitle={WADS}, year={1997} }

This paper addresses the problem of planning the motion of one or more pursuers in a polygonal environment to eventually “see” an evader that is unpredictable, has unknown initial position, and is capable of moving arbitrarily fast. This problem was first introduced by Suzuki and Yamashita. Our study of this problem is motivated in part by robotics applications, such as surveillance with a mobile robot equipped with a camera that must find a moving target in a cluttered workspace. A few bounds…

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## 223 Citations

Planning for robust visibility-based pursuit-evasion

- Computer Science2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
- 2020

This paper considers the case in which a pursuer with an omnidirectional sensor searches a known environment to locate an evader that may move arbitrarily quickly, and introduces the notion of an ε-robust solution strategy, in which ε is an upper bound on the positioning error that the pursuer may experience.

Visibility-Based Pursuit-Evasion in an Unknown Planar Environment

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A complete algorithm is presented that enables the limited pursuer to clear the same environments that a pursuer with a complete map, perfect localization, and perfect control can clear (under certain general position assumptions).

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The paper extends the three-dimensional cellular decomposition of Schwartz and Sharir to represent the four-dimensional configuration space of the pursuer-evader system, and derive necessary conditions for surveillance (equivalently, sufficient conditions for escape) in terms of this new representation.

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- 2017

This paper presents a complete algorithm that computes a minimum-cost pursuer trajectory that ensures that the evader is captured, or reports in finite time that no such trajectory exists, and describes an implementation of the algorithm, along with experiments that measure its performance in several environments with a variety of pruning operations.

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- Computer Science2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566)
- 2004

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This paper provides a constructive method to solve the decision problem of determining whether or not the pursuer is able to maintain strong mutual visibility of the evader, and proves decidability of this problem, and provides a complexity measure to this evader surveillance game.

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- Computer ScienceArXiv
- 2021

This paper studies a multi-robot visibility-based pursuit-evasion problem in which a group of pursuer robots are tasked with detecting an evader within a two dimensional polygonal environment and introduces an augmented data structure for encoding the problem state and a novel sampling technique to ensure that the generated plans are robust to failures of any single pursuer robot.

A complete algorithm for visibility-based pursuit-evasion with multiple pursuers

- Mathematics, Computer Science2014 IEEE International Conference on Robotics and Automation (ICRA)
- 2014

This work introduces a centralized algorithm for a visibility-based pursuit-evasion problem in a two-dimensional environment for the case of multiple pursuers and constructs a Pursuit Evasion Graph induced by the adjacency graph.

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An algorithm for a single pursuer with one flashlight searching for an unpredictable, moving target in a 213 environment using a representation called the visibility obstruction diagram and a decomposition of this diagram based on a skeleton that arises from critical visibility events is presented.

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- Computer Science2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
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This paper proposes an algorithm that can rapidly recover from catastrophic failures of a team of pursuer robots operating in a two-dimensional polygonal space and describes an implementation and provides quantitative results that show that the proposed method is able to recover from robot failures more rapidly than a baseline approach that plans from scratch.

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