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17
PursuitEvasion on Trees by Robot Teams
, 2010
"... We present GraphClear, a novel pursuitevasion problem on graphs which models the detection of intruders in complex indoor environments by robot teams. The environment is represented by a graph, and a robot team can execute sweep and block actions on vertices and edges respectively. A sweep action ..."
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Cited by 25 (4 self)
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We present GraphClear, a novel pursuitevasion problem on graphs which models the detection of intruders in complex indoor environments by robot teams. The environment is represented by a graph, and a robot team can execute sweep and block actions on vertices and edges respectively. A sweep action detects intruders in a vertex and represents the capability of the robot team to detect intruders in the region associated to the vertex. Similarly, a block action prevents intruders from crossing an edge and represents the capability to detect intruders as they move between regions. Both actions may require multiple robots to be executed. A strategy is a sequence of block and sweep actions detecting all intruders. When solving instances of GraphClear the goal is to determine optimal strategies, i.e. strategies using the least number of robots. We prove that for the general case of graphs the problem of computing optimal strategies is NPhard. Next, for the special case of trees we provide a polynomial time algorithm. The algorithm ensures that throughout the execution of the strategy all cleared vertices form a connected subtree, and we show it produces optimal strategies.
Multirobot surveillance: an improved algorithm for the graphclear problem
 In Proc. IEEE Intl. Conf. on Robotics and Automation
, 2008
"... Abstract—The main contribution of this paper is an improved algorithm for the GRAPHCLEAR problem, a novel NPcomplete graph theoretic problem we recently introduced as a tool to model multirobot surveillance tasks. The proposed algorithm combines two previously developed solving techniques and p ..."
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Cited by 20 (6 self)
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Abstract—The main contribution of this paper is an improved algorithm for the GRAPHCLEAR problem, a novel NPcomplete graph theoretic problem we recently introduced as a tool to model multirobot surveillance tasks. The proposed algorithm combines two previously developed solving techniques and produces strategies that require less robots to be executed. We provide a theoretical framework useful to identify the conditions for the existence of an optimal solution under special circumstances, and a set of mathematical tools characterizing the problem being studied. Finally we also identify a set of open questions deserving more investigations. I.
MSP Algorithm: MultiRobot Patrolling based on Territory Allocation using Balanced Graph Partitioning
"... This article addresses the problem of efficient multirobot patrolling in a known environment. The proposed approach assigns regions to each mobile agent. Every region is represented by a subgraph extracted from the topological representation of the global environment. A new algorithm is proposed in ..."
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Cited by 14 (10 self)
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This article addresses the problem of efficient multirobot patrolling in a known environment. The proposed approach assigns regions to each mobile agent. Every region is represented by a subgraph extracted from the topological representation of the global environment. A new algorithm is proposed in order to deal with the local patrolling task assigned for each robot, named Multilevel Subgraph Patrolling (MSP) Algorithm. It handles some major graph theory classic problems like graph partitioning, Hamilton cycles, nonHamilton cycles and longest path searches. The flexible, scalable, robust and high performance nature of this approach is testified by simulation results.
A Graph Search Algorithm for Indoor Pursuit / Evasion
, 2008
"... Using concepts from both robotics and graph theory, we formulate the problem of indoor pursuit / evasion in terms of searching a graph for a mobile evader. We present an offline, greedy, iterative algorithm which performs guaranteed search, i.e. no matter how the evader moves, it will eventually be ..."
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Cited by 9 (2 self)
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Using concepts from both robotics and graph theory, we formulate the problem of indoor pursuit / evasion in terms of searching a graph for a mobile evader. We present an offline, greedy, iterative algorithm which performs guaranteed search, i.e. no matter how the evader moves, it will eventually be captured; in fact our algorithm can be applied to either an adversarial (actively trying to avoid capture) or randomly moving evader. Furthermore the algorithm produces an internal search (the searchers move only along the edges of the graph, “teleporting” is not used) and can accommodate “extended” (across nodes) visibility and finite or infinite evader speed. We present search experiments for several indoor environments, some of them quite complicated, in all of which the algorithm succeeds in clearing the graph (i.e. capturing the evader).
Multi robot pursuit evasion without maps
 in Proc. IEEE Int. Conf. Robot. Autom. (ICRA
, 2010
"... Abstract—We propose a distributed algorithm enabling a large team of robots to detect all intruders within a large planar environment. Each robot can only detect intruders and communicate with other robots within a limited range. No map of the environment is given, and none is built during the proce ..."
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Cited by 9 (1 self)
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Abstract—We propose a distributed algorithm enabling a large team of robots to detect all intruders within a large planar environment. Each robot can only detect intruders and communicate with other robots within a limited range. No map of the environment is given, and none is built during the process. Robots are only capable of following walls and other robots that are nearby. The algorithm puts together elementary behaviors giving robots the means to coordinate their movement in order to cover lines between opposite walls with their sensors and discover nearby new walls. A line has leading robots at its endpoints that follow walls and hence move the line of robots forward. Multiple such lines move through the entire assigned area in order to detect all intruders. The movement of multiple lines is coordinated by using a graph representation of the environment that describes possible line movements and their associated costs in terms of robots. This coordination requires only local communication between the leaders of different robot lines when they meet. Finally, we demonstrate how the algorithm can be implemented using elementary wall following and obstacle discovery behaviors. I.
Probabilistic GraphClear
 In Proceedings of the IEEE International Conference on Robotics and Automation
, 2009
"... Abstract — This paper introduces a probabilistic model for multirobot surveillance applications with limited range and possibly faulty sensors. Sensors are described with a footprint and a false negative probability, i.e. the probability of failing to report a target within their sensing range. The ..."
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Cited by 6 (3 self)
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Abstract — This paper introduces a probabilistic model for multirobot surveillance applications with limited range and possibly faulty sensors. Sensors are described with a footprint and a false negative probability, i.e. the probability of failing to report a target within their sensing range. The model implements a probabilistic extension to our formerly developed deterministic approach for modeling surveillance tasks in large environments with large robot teams known as GraphClear. This extension leads to a new algorithm that allows to answer new design and performance questions, namely 1) how many robots are needed to obtain a certain confidence that the environment is free from intruders, and 2) given a certain number of robots, how should they coordinate their actions to minimize their failure rate. I.
Demonstration of MultiRobot Search and Secure
 In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA’10)  Workshop on Search and Pursuit/Evasion in the Physical World: Efficiency, Scalability, and Guarantees
, 2010
"... AbstractWe consider the search and secure problem, where intruders are to be detected in a bounded area without allowing them to escape. The problem is tackled by representing the area to be searched as a traversability graph, which is reduced to a tree graph by placing stationary robots to remove ..."
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Cited by 4 (0 self)
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AbstractWe consider the search and secure problem, where intruders are to be detected in a bounded area without allowing them to escape. The problem is tackled by representing the area to be searched as a traversability graph, which is reduced to a tree graph by placing stationary robots to remove loops. The search of the remaining tree is performed using two strategies that represent different tradeoffs between the needed search time and the number of robots. Proof of correctness is provided for these two strategies. The proposed algorithm was implemented and demonstrated as part of an outeld experiment involving a team of Rotundus spherical robots.
Intelligent Pursuit and Evasion in an Unknown Environment
 In Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS’09
, 2009
"... AbstractThis paper introduces a novel and flexible simulation platform for studying pursuit and evasion in unknown 2D environments of arbitrary obstacles, in an effort to expand the practical application of pursuitevasion research. The platform provides realistic simulation of the sensing capabi ..."
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Cited by 2 (0 self)
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AbstractThis paper introduces a novel and flexible simulation platform for studying pursuit and evasion in unknown 2D environments of arbitrary obstacles, in an effort to expand the practical application of pursuitevasion research. The platform provides realistic simulation of the sensing capability of each robotic agent (either a pursuer or an evader). Each agent uses realtime local sensing to collect information from the environment while it simultaneously plans and executes its motion to best satisfy one or more objectives. The evader's objectives are to reach a specific goal location as quickly as possible and to avoid being caught by the pursuer. The pursuer's objectives are to locate and capture the evader whose motion is unknown, and when the evader is not seen, explore the environment and predict where the evader may be. Under a common realtime planning paradigm, each agent's planner dynamically adapts its goals and objectives to the agent's changing circumstances so that the agent can always choose the best course of action. Simulation results have shown that the introduced approach is an effective means to study sophisticated pursuitevasion scenarios and accomplish objectives for both the pursuer and the evader in an unknown environment. The platform can be easily expanded to accommodate multiple agents in more complex pursuitevasion tasks.
D.: Environment characterization for nonrecontaminating frontierbased robotic exploration (full version
, 2011
"... Abstract. This paper addresses the problem of obtaining a concise description of a physical environment for robotic exploration. We aim to determine the number of robots required to clear an environment using nonrecontaminating exploration. We introduce the medial axis as a configuration space and ..."
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Cited by 1 (1 self)
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Abstract. This paper addresses the problem of obtaining a concise description of a physical environment for robotic exploration. We aim to determine the number of robots required to clear an environment using nonrecontaminating exploration. We introduce the medial axis as a configuration space and derive a mathematical representation of a continuous environment that captures its underlying topology and geometry. We show that this representation provides a concise description of arbitrary environments, and that reasoning about points in this representation is equivalent to reasoning about robots in physical space. We leverage this to derive a lower bound on the number of required pursuers. We provide a transformation from this continuous representation into a symbolic representation. Finally, we present a generalized pursuitevasion algorithm. Given an environment we can compute how many pursuers we need, and generate an optimal pursuit strategy that will guarantee the evaders are detected with the minimum number of pursuers.
An Iterative Mixed Integer Linear Programming Approach to Pursuit Evasion Problems in Polygonal Environments
"... AbstractIn this paper, we address the multi pursuer version of the pursuit evasion problem in polygonal environments. It is well known that this problem is NPhard, and therefore we seek efficient, but not optimal, solutions by relaxing the problem and applying the tools of Mixed Integer Linear Pr ..."
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AbstractIn this paper, we address the multi pursuer version of the pursuit evasion problem in polygonal environments. It is well known that this problem is NPhard, and therefore we seek efficient, but not optimal, solutions by relaxing the problem and applying the tools of Mixed Integer Linear Programming (MILP) and Receding Horizon Control (RHC). Approaches using MILP and RHC are known to produce efficient algorithms in other path planning domains, such as obstacle avoidance. Here we show how the MILP formalism can be used in a pursuit evasion setting to capture the motion of the pursuers as well as the partitioning of the pursuit search region into a cleared and a contaminated part. RHC is furthermore a well known way of balancing performance and computation requirements by iteratively solving path planning problems over a receding planning horizon, and adapt the length of that horizon to the computational resources available. The proposed approach is implemented in Matlab/Cplex and illustrated by a number of solved examples.