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MultiRobot Perimeter Patrol in Adversarial Settings
"... This paper considers the problem of multirobot patrol around a closed area with the existence of an adversary attempting to penetrate into the area. In case the adversary knows the patrol scheme of the robots and the robots use a deterministic patrol algorithm, then in many cases it is possible to ..."
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Cited by 88 (22 self)
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This paper considers the problem of multirobot patrol around a closed area with the existence of an adversary attempting to penetrate into the area. In case the adversary knows the patrol scheme of the robots and the robots use a deterministic patrol algorithm, then in many cases it is possible to penetrate with probability 1. Therefore this paper considers a nondeterministic patrol scheme for the robots, such that their movement is characterized by a probability p. This patrol scheme allows reducing the probability of penetration, even under an assumption of a strong opponent that knows the patrol scheme. We offer an optimal polynomialtime algorithm for finding the probability p such that the minimal probability of penetration detection throughout the perimeter is maximized. We describe three robotic motion models, defined by the movement characteristics of the robots. The algorithm described herein is suitable for all three models.
The Impact of Adversarial Knowledge on Adversarial Planning in Perimeter Patrol
, 2008
"... This paper considers the problem of multirobot patrolling around a closed area, in the presence of an adversary trying to penetrate the area. Previous work on planning in similar adversarial environments addressed worstcase settings, in which the adversary has full knowledge of the defending robot ..."
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Cited by 34 (14 self)
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This paper considers the problem of multirobot patrolling around a closed area, in the presence of an adversary trying to penetrate the area. Previous work on planning in similar adversarial environments addressed worstcase settings, in which the adversary has full knowledge of the defending robots. It was shown that non deterministic algorithms may be effectively used to maximize the chances of blocking such a fullknowledge opponent, and such algorithms guarantee a “lower bound” to the performance of the team. However, an open question remains as to the impact of the knowledge of the opponent on the performance of the robots. This paper explores this question in depth and provides theoretical results, supported by extensive experiments with 68 human subjects concerning the compatibility of algorithms to the extent of information possessed
Persistent Robotic Tasks: Monitoring and Sweeping in Changing Environments
, 2011
"... We present controllers that enable mobile robots to persistently monitor or sweep a changing environment. The changing environment is modeled as a field which grows in locations that are not within range of a robot, and decreases in locations that are within range of a robot. We assume that the rob ..."
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Cited by 34 (10 self)
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We present controllers that enable mobile robots to persistently monitor or sweep a changing environment. The changing environment is modeled as a field which grows in locations that are not within range of a robot, and decreases in locations that are within range of a robot. We assume that the robots travel on given closed paths. The speed of each robot along its path is controlled to prevent the field from growing unbounded at any location. We consider the space of speed controllers that can be parametrized by a finite set of basis functions. For a single robot, we develop a linear program that is guaranteed to compute a speed controller in this space to keep the field bounded, if such a controller exists. Another linear program is then derived whose solution is the speed controller that minimizes the maximum field value over the environment. We extend our linear program formulation to develop a multirobot controller that keeps the field bounded. The multirobot controller has the unique feature that it does not require communication among the robots. Simulation studies demonstrate the robustness of the controllers to modeling errors, and to stochasticity in the environment.
On optimal cooperative patrolling
 in IEEE Conf. on Decision and Control
, 2010
"... Abstract — This work considers the problem of designing optimal multiagent trajectories to patrol an environment. As performance criterion for optimal patrolling we consider the worstcase time gap between any two visits of the same region. We represent the area to be patrolled with a graph, and we ..."
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Cited by 14 (3 self)
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Abstract — This work considers the problem of designing optimal multiagent trajectories to patrol an environment. As performance criterion for optimal patrolling we consider the worstcase time gap between any two visits of the same region. We represent the area to be patrolled with a graph, and we characterize the computational complexity of the trajectory design (patrolling) problem with respect to the environment topology and to the number of robots employed in the patrolling task. Even though the patrolling problem is generally NPhard, we identify particular cases that are solvable efficiently, and we describe optimal patrolling trajectories. Finally, we present a heuristic with performance guarantees, and an 8approximation algorithm to solve the NPhard patrolling problem. 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.
Multirobot adversarial patrolling: Facing a fullknowledge opponent
 Journal of Artificial Intelligence Research
"... Abstract The problem of adversarial multirobot patrol has gained interest in recent years, mainly due to its immediate relevance to various security applications. In this problem, robots are required to repeatedly visit a target area in a way that maximizes their chances of detecting an adversary ..."
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Cited by 11 (2 self)
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Abstract The problem of adversarial multirobot patrol has gained interest in recent years, mainly due to its immediate relevance to various security applications. In this problem, robots are required to repeatedly visit a target area in a way that maximizes their chances of detecting an adversary trying to penetrate through the patrol path. When facing a strong adversary that knows the patrol strategy of the robots, if the robots use a deterministic patrol algorithm, then in many cases it is easy for the adversary to penetrate undetected (in fact, in some of those cases the adversary can guarantee penetration). Therefore this paper presents a nondeterministic patrol framework for the robots. Assuming that the strong adversary will take advantage of its knowledge and try to penetrate through the patrol's weakest spot, hence an optimal algorithm is one that maximizes the chances of detection in that point. We therefore present a polynomialtime algorithm for determining an optimal patrol under the Markovian strategy assumption for the robots, such that the probability of detecting the adversary in the patrol's weakest spot is maximized. We build upon this framework and describe an optimal patrol strategy for several robotic models based on their movement abilities (directed or undirected) and sensing abilities (perfect or imperfect), and in different environment models either patrol around a perimeter (closed polygon) or an open fence (open polyline).
Cassandras, “An optimal control approach to the multiagent persistent monitoring problem in twodimensional spaces
 in Proc. of 52nd IEEE Conf. Decision and Control, 2013
"... AbstractWe present an optimal control framework for persistent monitoring problems where the objective is to control the movement of multiple cooperating agents to minimize an uncertainty metric in a given mission space. In a onedimensional mission space, we show that the optimal solution is for ..."
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Cited by 9 (1 self)
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AbstractWe present an optimal control framework for persistent monitoring problems where the objective is to control the movement of multiple cooperating agents to minimize an uncertainty metric in a given mission space. In a onedimensional mission space, we show that the optimal solution is for each agent to move at maximal speed from one switching point to the next, possibly waiting some time at each point before reversing its direction. Thus, the solution is reduced to a simpler parametric optimization problem: determining a sequence of switching locations and associated waiting times at these switching points for each agent. This amounts to a hybrid system which we analyze using Infinitesimal Perturbation Analysis (IPA) to obtain a complete online solution through a gradientbased algorithm. We also show that the solution is robust with respect to the uncertainty model used. This establishes the basis for extending this approach to a twodimensional mission space.
A survey on multirobot patrolling algorithms,” Technological Innovation for Sustainability
, 2011
"... Abstract. This article presents a survey on cooperative multirobot patrolling algorithms, which is a recent field of research. Every strategy proposed in the last decade is distinct and is normally based on operational research methods, simple and classic techniques for agent’s coordination or alte ..."
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Cited by 8 (3 self)
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Abstract. This article presents a survey on cooperative multirobot patrolling algorithms, which is a recent field of research. Every strategy proposed in the last decade is distinct and is normally based on operational research methods, simple and classic techniques for agent’s coordination or alternative, and usually more complex, coordination mechanisms like marketbased approaches or reinforcementlearning. The variety of approaches differs in various aspects such as agent type and their decisionmaking or the coordination and communication mechanisms. Considering the current work concerning the patrolling problem with teams of robots, it is felt that there is still a great potential to take a step forward in the knowledge of this field, approaching wellknown limitations in previous works that should be overcome.
Persistent monitoring in discrete environments: Minimizing the maximum weighted latency between observations,”
 The International Journal of Robotics Research,
, 2014
"... Abstract In this paper, we consider the problem of planning a path for a robot to monitor a known set of features of interest in an environment. We represent the environment as a graph with vertex weights and edge lengths. The vertices represent regions of interest, edge lengths give travel times b ..."
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Cited by 7 (0 self)
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Abstract In this paper, we consider the problem of planning a path for a robot to monitor a known set of features of interest in an environment. We represent the environment as a graph with vertex weights and edge lengths. The vertices represent regions of interest, edge lengths give travel times between regions, and the vertex weights give the importance of each region. As the robot repeatedly performs a closed walk on the graph, we define the weighted latency of a vertex to be the maximum time between visits to that vertex, weighted by the importance (vertex weight) of that vertex. Our goal is to find a closed walk that minimizes the maximum weighted latency of any vertex. We show that there does not exist a polynomial time algorithm for the problem. We then provide two approximation algorithms; an O(log n)approximation algorithm and an O(log ρ G )approximation algorithm, where ρ G is the ratio between the maximum and minimum vertex weights. We provide simulation results which demonstrate that our algorithms can be applied to problems consisting of thousands of vertices, and a case study for patrolling a city for crime.
Sustainable MultiRobot Patrol of an Open Polyline
"... Abstract — We present an algorithm that maintains coverage of an open polyline patrolled by a team of robots. While previous work has focused on the uniformity of patrolling, we focus on ensuring the longevity of the system in the face of robot failures. A central control tower monitors the battery ..."
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Cited by 6 (0 self)
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Abstract — We present an algorithm that maintains coverage of an open polyline patrolled by a team of robots. While previous work has focused on the uniformity of patrolling, we focus on ensuring the longevity of the system in the face of robot failures. A central control tower monitors the battery levels of the robots, and recalls them when they are low on power replacing them with fully charged robots. We compare two methods for replacement, both of which aim to keep coverage interruptions to a minimum. We present results obtained through physical experiments and simulations. I.