Toward Intelligent Security Robots: A Survey

Theodoridis, Theodoros; Hu, Huosheng

doi:10.1109/tsmcc.2012.2198055

Cited by 42 publications

(27 citation statements)

References 40 publications

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“…CT is suitable when the number of targets does not considerably exceed the number of robots and there might be the need of close observation of some specific targets, e.g. using security robots [102].…”

Section: A Cooperative Tracking (Ct)mentioning

confidence: 99%

Cooperative Robots to Observe Moving Targets: Review

Khan

Rinner

Cavallaro

2018

IEEE Trans. Cybern.

162

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The deployment of multiple robots for achieving a common goal helps to improve the performance, efficiency, and/or robustness in a variety of tasks. In particular, the observation of moving targets is an important multirobot application that still exhibits numerous open challenges, including the effective coordination of the robots. This paper reviews control techniques for cooperative mobile robots monitoring multiple targets. The simultaneous movement of robots and targets makes this problem particularly interesting, and our review systematically addresses this cooperative multirobot problem for the first time. We classify and critically discuss the control techniques: cooperative multirobot observation of multiple moving targets, cooperative search, acquisition, and track, cooperative tracking, and multirobot pursuit evasion. We also identify the five major elements that characterize this problem, namely, the coordination method, the environment, the target, the robot and its sensor(s). These elements are used to systematically analyze the control techniques. The majority of the studied work is based on simulation and laboratory studies, which may not accurately reflect real-world operational conditions. Importantly, while our systematic analysis is focused on multitarget observation, our proposed classification is useful also for related multirobot applications.

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Section: A Cooperative Tracking (Ct)mentioning

confidence: 99%

Cooperative Robots to Observe Moving Targets: Review

Khan

Rinner

Cavallaro

2018

IEEE Trans. Cybern.

162

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“…(cx n , 2y n ); 0 y n 0.5 B (x n ,y n ) = where 0 < c < 0.5 (1) (1+c (x n -1), 2y n -1); 0.5 < y n 1…”

Section: Along Xaxis Along Yaxismentioning

confidence: 99%

“…There has been a recent growth in the use of autonomous patrol & surveillance robots in civil and military applications [1,2]. Besides mobile, patrol robots are also commercially available today, for e.g.…”

Section: Introductionmentioning

confidence: 99%

Chaotic patrol robot with frequency constraints

Banerjee

Datta

Agarwal

2015

2015 IEEE International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN)

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Patrol or surveillance robots follow a trajectory that should be hard to predict. Dynamic nonlinear systems like chaotic systems are popularly used for generating pseudorandom trajectory for patrol robots. Due to apparently random nature of the trajectory, the presence of the robot at a certain region of the target area becomes infrequent. These point visit frequencies needs to be bounded or constrained so that a certain region is not left unmonitored for a long duration. In this paper we provide a proper survey of the issue. We also propose an approach that dynamically infuses separately generated chaotic coordinates into the original trajectory, such that the robot visits every significant part of the area at least once within a certain time. We also keep in check that the overall randomness of the system is not compromised.

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“…Multirobot systems are expected to undertake imperative roles in a wide variety of fields such as urban search and rescue (USAR) [1,2], agricultural field operations [3], security patrols [4,5], environmental monitoring [6], and industrial procedures [7]. Studies have shown that multi-robot systems have advantage over single-robot systems by offering more reliability, redundancy, and time efficiency when the nature of the tasks is inherently distributed [8].…”

Section: Introductionmentioning

confidence: 99%

Multiagent Task Allocation in Complementary Teams: A Hunter-and-Gatherer Approach

et al. 2020

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Consider a dynamic task allocation problem, where tasks are unknowingly distributed over an environment. This paper considers each task comprised of two sequential subtasks: detection and completion, where each subtask can only be carried out by a certain type of agent. We address this problem using a novel nature-inspired approach called "hunter and gatherer". The proposed method employs two complementary teams of agents: one agile in detecting (hunters) and another dexterous in completing (gatherers) the tasks. To minimize the collective cost of task accomplishments in a distributed manner, a game-theoretic solution is introduced to couple agents from complementary teams. We utilize market-based negotiation models to develop incentive-based decision-making algorithms relying on innovative notions of "certainty and uncertainty profit margins". The simulation results demonstrate that employing two complementary teams of hunters and gatherers can effectually improve the number of tasks completed by agents compared to conventional methods, while the collective cost of accomplishments is minimized. In addition, the stability and efficacy of the proposed solutions are studied using Nash equilibrium analysis and statistical analysis respectively. It is also numerically shown that the proposed solutions function fairly, i.e. for each type of agent, the overall workload is distributed equally.Index Terms-Distributed multiagent system, dynamic task allocation, game theory, negotiation. I. INTRODUCTIONMultirobot systems are expected to undertake imperative roles in a wide variety of fields such as urban search and rescue (USAR) [1,2], agricultural field operations [3], security patrols [4,5], environmental monitoring [6], and industrial procedures [7]. Studies have shown that multi-robot systems have advantage over single-robot systems by offering more reliability, redundancy, and time efficiency when the nature of the tasks is inherently distributed [8]. Nonetheless, the problem of multi-robot task-allocation (MRTA) poses many critical challenges that has called for investigation in the past two decades [9][10][11]. In this regards, the complexity of MRTA problems increases significantly in a dynamic environment, where the number and location of tasks are unknown for agents [12,13]. Thus, robots need to explore the environment to find tasks before accomplishing them. In real world problems, any robot designated to perform one of the tasks in [1-7] needs to be sufficiently dexterous which makes it relatively heavy and incapable of agile exploration. Having said that, the dynamic problem can be turned into a problem where each task is comprised of sequential subtasks, each possible to be done only by a certain type of agent. In that case, for each type of subtask, a robot team of appropriate type must be employed. This case poses an unexplored MRTA problem whose coupling and cooperation between those complementary teams is the motivation of this work.In the context of MRTA, notable attention has been devoted for revealing ...

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Toward Intelligent Security Robots: A Survey

Cited by 42 publications

References 40 publications

Cooperative Robots to Observe Moving Targets: Review

Cooperative Robots to Observe Moving Targets: Review

Chaotic patrol robot with frequency constraints

Multiagent Task Allocation in Complementary Teams: A Hunter-and-Gatherer Approach

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