Distributed Online Patrolling with Multi-agent Teams of Sentinels and Searchers

Basilico, Nicola; Chung, Timothy H.; Carpin, Stefano

doi:10.1007/978-4-431-55879-8_1

Cited by 7 publications

(3 citation statements)

References 14 publications

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“…The resulting uncertainties are reflected in the probability of UAVs detecting the illegal immigrant in each patrol area. Similar research on UAV detection probability includes introducing a variable resolution sensing model to address the problem of variable probability of UAV detection, which is suitable for the online patrol with uniform grids [36]. On this basis, how heterogeneous UAVs cooperate in patrolling designated areas was analyzed, and different sensor models were introduced to predict the optimal patrol team size and performance configuration [37].…”

Section: Related Workmentioning

confidence: 99%

A multi-UAV deployment method for border patrolling based on Stackelberg game

Liu

Wang

et al. 2023

J. of Syst. Eng. Electron.

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To strengthen border patrol measures, unmanned aerial vehicles (UAVs) are gradually used in many countries to detect illegal entries on borders. However, how to efficiently deploy limited UAVs to patrol on borders of large areas remains challenging. In this paper, we first model the problem of deploying UAVs for border patrol as a Stackelberg game. Two players are considered in this game: The border patrol agency is the leader, who optimizes the patrol path of UAVs to detect the illegal immigrant. The illegal immigrant is the follower, who selects a certain area of the border to pass through at a certain time after observing the leader 's strategy. Second, a compact linear programming problem is proposed to tackle the exponential growth of the number of leader's strategies. Third, a method is proposed to reduce the size of the strategy space of the follower. Then, we provide some theoretic results to present the effect of parameters of the model on leader's utilities. Experimental results demonstrate the positive effect of limited starting and ending areas of UAV's patrolling conditions and multiple patrolling altitudes on the leader 's utility, and show that the proposed solution outperforms two conventional patrol strategies and has strong robustness.

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Section: Related Workmentioning

confidence: 99%

A multi-UAV deployment method for border patrolling based on Stackelberg game

Liu

Wang

et al. 2023

J. of Syst. Eng. Electron.

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“…Bullo et al model the problem as queues and provide performance bounds in light and heavy traffic. Basilico et al examines the performance of robotic drones that patrol a given area. The robots are of multiple types.…”

Section: Literature Reviewmentioning

confidence: 99%

Same‐day delivery with heterogeneous fleets of drones and vehicles

2018

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In this paper, we analyze how drones can be combined with regular delivery vehicles to improve same‐day delivery performance. To this end, we present a dynamic vehicle routing problem with heterogeneous fleets. Customers order goods over the course of the day. These goods are delivered either by a drone or by a regular transportation vehicle within a delivery deadline. Drones are faster, but have a limited capacity as well as require charging after use. In the same‐day context, vehicle capacity is not a constraint, but vehicles are slow due to urban traffic. To decide whether an order is delivered by a drone or by a vehicle, we present a policy function approximation based on geographical districting. Our computational study reveals two major implications. First, geographical districting is highly effective increasing the expected number of same‐day deliveries. Second, a combination of drone and vehicle fleets may significantly reduce the required delivery resources.

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“…Often, in large environments, a constant surveillance of every area is not affordable while focused inspections triggered by alarms are more convenient. Realworld applications include UAVs surveillance of large infrastructures [19], wildfires detection with CCD cameras [20], agricultural fields monitoring [21], and surveillance based on wireless sensor networks [22], and border patrolling [23]. Alarm systems are in practice affected by detection uncertainty, e.g., missed detections and false positives, and localization (a.k.a.…”

Section: Motivation Scenariosmentioning

confidence: 99%

Adversarial patrolling with spatially uncertain alarm signals

Basilico

Nittis

Gatti

2017

Artificial Intelligence

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When securing complex infrastructures or large environments, constant surveillance of every area is not affordable. To cope with this issue, a common countermeasure is the usage of cheap but wide-ranged sensors, able to detect suspicious events that occur in large areas, supporting patrollers to improve the effectiveness of their strategies. However, such sensors are commonly affected by uncertainty. In the present paper, we focus on spatially uncertain alarm signals. That is, the alarm system is able to detect an attack but it is uncertain on the exact position where the attack is taking place. This is common when the area to be secured is wide, such as in border patrolling and fair site surveillance. We propose, to the best of our knowledge, the first Patrolling Security Game where a Defender is supported by a spatially uncertain alarm system, which non-deterministically generates signals once a target is under attack. We show that finding the optimal strategy is FNP-hard even in tree graphs and APX-hard in arbitrary graphs. We provide two (exponential time) exact algorithms and two (polynomial time) approximation algorithms. Finally, we show that, without false positives and missed detections, the best patrolling strategy reduces to stay in a place, wait for a signal, and respond to it at best. This strategy is optimal even with non-negligible missed detection rates, which, unfortunately, affect every commercial alarm system. We evaluate our methods in simulation, assessing both quantitative and qualitative aspects.

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Distributed Online Patrolling with Multi-agent Teams of Sentinels and Searchers

Cited by 7 publications

References 14 publications

A multi-UAV deployment method for border patrolling based on Stackelberg game

A multi-UAV deployment method for border patrolling based on Stackelberg game

Same‐day delivery with heterogeneous fleets of drones and vehicles

Adversarial patrolling with spatially uncertain alarm signals

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