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Visibilitybased pursuitevasion in an unknown planar environment
 International Journal of Robotics Research
, 2004
"... We address an online version of the visibilitybased pursuitevasion problem. We take a minimalist approach in modeling the capabilities of a pursuer robot. A point pursuer moves in an unknown, simplyconnected, piecewisesmooth planar environment, and is given the task of locating any unpredictable ..."
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Cited by 49 (8 self)
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We address an online version of the visibilitybased pursuitevasion problem. We take a minimalist approach in modeling the capabilities of a pursuer robot. A point pursuer moves in an unknown, simplyconnected, piecewisesmooth planar environment, and is given the task of locating any unpredictable, moving evaders that have unbounded speed. The evaders are assumed to be points that move continuously. To solve the problem, the pursuer must for each target have an unobstructed view of it at some time during execution. The pursuer is equipped with a range sensor that measures the direction of depth discontinuities, but cannot provide precise depth measurements. All pursuer control is specified either in terms of this sensor or wallfollowing movements. The pursuer does not have localization capability or perfect control. We present a complete algorithm 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). Theoretical guarantees that the evaders will be found are provided. The resulting algorithm to compute this strategy has been implemented in simulation. Results are shown for several examples. The approach is efficient and simple enough to be useful towards the development of real robot systems that perform visual searching. 1
A pursuitevasion BUG algorithm
 In Proc. IEEE Int’l Conf. on Robotics and Automation
, 1954
"... We consider the problem of searching for an unpredictable moving target, using a robot that lacks a map of the environment, lacks the ability to construct a map, and has imperfect navigation ability. We present a complete algorithm, which yields a motion strategy for the robot that guarantees the el ..."
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Cited by 20 (13 self)
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We consider the problem of searching for an unpredictable moving target, using a robot that lacks a map of the environment, lacks the ability to construct a map, and has imperfect navigation ability. We present a complete algorithm, which yields a motion strategy for the robot that guarantees the elusive target will be detected, if such a strategy exists. It is assumed that the robot has an omnidirectional sensing device that is used to detect moving targets and also discontinuities in depth data in a 2D environment. We also show that the robot has the same problemsolving power as a robot that has a complete map and perfect navigation abilities. The algorithm has been implemented in simulation, and some examples are shown. 1
A COMPLETE ALGORITHM FOR SEARCHLIGHT SCHEDULING
, 2011
"... This article develops an algorithm for a group of guards statically positioned in a nonconvex polygonal environment with holes. Each guard possesses a single searchlight, a ray sensor which can rotate about the guard’s position but cannot penetrate the boundary of the environment. A point is detecte ..."
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Cited by 7 (1 self)
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This article develops an algorithm for a group of guards statically positioned in a nonconvex polygonal environment with holes. Each guard possesses a single searchlight, a ray sensor which can rotate about the guard’s position but cannot penetrate the boundary of the environment. A point is detected by a searchlight if and only if the point is on the ray at some instant. Targets are points which move arbitrarily fast. The objective of the proposed algorithm is to compute a schedule to rotate a set of searchlights in such a way that any target in an environment will necessarily be detected in finite time. This is known as the Searchlight Scheduling Problem and was described originally in 1990 by Sugihara et al. We take an approach known as exact cell decomposition in the motion planning literature. The algorithm operates by decomposing the searchlights ’ joint configuration space and the environment, and then by constructing a socalled information graph. Searching the information graph for a path between desired states yields a search schedule. We also introduce a new problem called the φSearchlight Scheduling Problem in which φsearchlights sense not just along a ray, but over a finite field of view. We show that our results for searchlight scheduling can be directly extended for φsearchlight scheduling. Proofs of completeness, complexity bounds, and computed examples are presented.
A Complete PursuitEvasion Algorithm for Two Pursuers Using Beam Detection
 in IEEE International Conference on Robotics and Automation, 2002
, 2002
"... We present an algorithm for a pair of pursuers, each with one rotating beam (flashlight, laser or a camera), searching for an unpredictable, moving target in a 2D environment (simple polygon). Given a polygon with n edges, the algorithm decides in time O(n ) whether it can be cleared by the pursu ..."
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Cited by 5 (2 self)
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We present an algorithm for a pair of pursuers, each with one rotating beam (flashlight, laser or a camera), searching for an unpredictable, moving target in a 2D environment (simple polygon). Given a polygon with n edges, the algorithm decides in time O(n ) whether it can be cleared by the pursuers, and if so, constructs a search schedule. The pursuers are allowed to move on the boundary and in the interior of the polygon. They are not required to maintain mutual visibility throughout the pursuit.
Clearing a Polygon with Two 1searchers
, 2003
"... We present an algorithm for a pair of pursuers, each with one flashlight, searching for an unpredictable, moving target in a 2D environment (simple polygon). Given a polygon with n edges, the algorithm decides in time O(n ) whether it can be cleared by the pursuers, and if so, constructs a sea ..."
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Cited by 4 (0 self)
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We present an algorithm for a pair of pursuers, each with one flashlight, searching for an unpredictable, moving target in a 2D environment (simple polygon). Given a polygon with n edges, the algorithm decides in time O(n ) whether it can be cleared by the pursuers, and if so, constructs a search schedule. The pursuers are allowed to move on the boundary and in the interior of the polygon. They are not required to maintain mutual visibility throughout the pursuit.
Asynchronous distributed searchlight scheduling
, 2007
"... Abstract — This paper develops and compares two asynchronous distributed scheduling algorithms for multiple controlled searchlights in nonconvex polygonal environments. A searchlight is a ray emitted by source location that (i) cannot penetrate the boundary of the environment and (ii) undergoes cont ..."
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Cited by 3 (3 self)
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Abstract — This paper develops and compares two asynchronous distributed scheduling algorithms for multiple controlled searchlights in nonconvex polygonal environments. A searchlight is a ray emitted by source location that (i) cannot penetrate the boundary of the environment and (ii) undergoes controlled slewing about its source location. Evaders move inside the environment along continuous trajectories and are detected precisely when they are on the searchlight ray at some time instant. The objective is for the searchlights to detect any evader in finite time and to do so using only local sensing and limited communication among them. The first algorithm we develop, called the Distributed One Way Sweep Strategy (DOWSS), is a distributed version of an algorithm described originally in 1990 by Sugihara et al [1]; this algorithm may be slow in “sweeping ” the environment because only one searchlight slews at a time. Second we develop an algorithm, called the Parallel Tree Sweep Strategy (PTSS), in which searchlights sweep concurrently under the assumption that they are placed in appropriate locations; for this algorithm we establish linear completion time. I.
Mapping and PursuitEvasion Strategies For a Simple WallFollowing Robot
"... This paper defines and analyzes a simple robot with local sensors that moves in an unknown polygonal environment. The robot can execute wallfollowing motions and can traverse the interior of the environment only when following parallel to an edge. The robot has no global sensors that would allow pr ..."
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Cited by 1 (1 self)
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This paper defines and analyzes a simple robot with local sensors that moves in an unknown polygonal environment. The robot can execute wallfollowing motions and can traverse the interior of the environment only when following parallel to an edge. The robot has no global sensors that would allow precise mapping or localization. Special information spaces are introduced for this particular model. Using these, strategies are presented for solving several tasks: 1) counting vertices, 2) computing the path winding number, 3) learning a combinatorial map, called the cut ordering, that encodes partial geometric information, and 4) solving pursuitevasion problems.
Shadow Information Spaces: Combinatorial Filters for Tracking Targets
"... This paper introduces and solves a problem of maintaining the distribution of hidden targets that move outside the field of view while a sensor sweep is being performed, resulting in a generalization of the sensing aspect of visibilitybased pursuitevasion games. Our solution first applies informat ..."
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Cited by 1 (1 self)
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This paper introduces and solves a problem of maintaining the distribution of hidden targets that move outside the field of view while a sensor sweep is being performed, resulting in a generalization of the sensing aspect of visibilitybased pursuitevasion games. Our solution first applies information space concepts to significantly reduce the general complexity so that information is processed only when the shadow region (all points invisible to the sensors) changes combinatorially or targets pass in and out of the field of view. The cases of distinguishable, partially distinguishable, and completely indistinguishable targets are handled. Depending on whether the targets move nondeterministically or probabilistically, more specific classes of problems are formulated. For each case, efficient filtering algorithms are introduced, implemented, and demonstrated that provide critical information for tasks such as counting, herding, pursuitevasion, and situational awareness.
ESP: Pursuit Evasion on SeriesParallel Graphs
, 2010
"... We study pursuitevasion problems where pursuers have to clear a given graph of fastmoving evaders despite poor visibility, for example, where police search a cave system to ensure that no terrorists are hiding in it. If the vertex connectivity of some part of the graph exceeds the number of pursue ..."
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We study pursuitevasion problems where pursuers have to clear a given graph of fastmoving evaders despite poor visibility, for example, where police search a cave system to ensure that no terrorists are hiding in it. If the vertex connectivity of some part of the graph exceeds the number of pursuers, the evaders can always avoid capture. We therefore focus on graphs whose subgraphs can always be cut at a limited number of vertices, that is, graphs of low treewidth. However, solving pursuitevasion problems optimally is NPhard even for the simplest of these graph classes. In this paper, we therefore develop a heuristic approach, called ESP, that solves large pursuitevasion problems on seriesparallel (that is, treewidthtwo) graphs quickly and with small costs. It exploits their topology by performing dynamic programming on their decomposition graphs. We apply ESP to different kinds of seriesparallel graphs and show that it scales up to larger graphs than a strawman approach based on previous results from the literature.