Coverage Control for Mobile Sensing Networks

Cortés, Jorge; Martínez, Sònia; Karatas, Timur; Bullo, Francesco

doi:10.1109/tra.2004.824698

“…More importantly, the analytical bounds on these weights can provably limit the illeffects of spoofers on the performance of these controllers. This paper demonstrates this capability in the context of the well-known locational coverage algorithm [6,31].…”

Section: Fig 1: Sybil Attack On Coveragementioning

confidence: 86%

Guaranteeing Spoof-Resilient Multi-Robot Networks

Gil

¹

,

Kumar

²

,

Mazumder

³

et al. 2015

Robotics: Science and Systems XI

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Abstract-Multi-robot networks use wireless communication to provide wide-ranging services such as aerial surveillance and unmanned delivery. However, effective coordination between multiple robots requires trust, making them particularly vulnerable to cyber-attacks. Specifically, such networks can be gravely disrupted by the Sybil attack, where even a single malicious robot can spoof a large number of fake clients. This paper proposes a new solution to defend against the Sybil attack, without requiring expensive cryptographic key-distribution. Our core contribution is a novel algorithm implemented on commercial Wi-Fi radios that can "sense" spoofers using the physics of wireless signals. We derive theoretical guarantees on how this algorithm bounds the impact of the Sybil Attack on a broad class of robotic coverage problems. We experimentally validate our claims using a team of AscTec quadrotor servers and iRobot Create ground clients, and demonstrate spoofer detection rates over 96%.

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“…In doing so, it provides theoretical security guarantees that are validated experimentally. These integrate readily with performance guarantees of existing multi-robot controllers, like the well-known robotic coverage controllers [6,31] as shown in Sec. §VI.…”

Section: Related Workmentioning

confidence: 96%

“…Multi-robot networks rely on wireless communication to enable a wide range of tasks and applications: coverage [28,6,31], disaster management [7], surveillance [4], and consensus [27] to name a few. The future promises an increasing trend in this direction, such as delivery drones which transport goods (e.g., Amazon Prime Air [2]) or traffic rerouting algorithms (e.g., Google Maps Navigation) that rely on broadcasted user locations to achieve their goals.…”

Section: Introductionmentioning

confidence: 99%

Guaranteeing spoof-resilient multi-robot networks

Gil

¹

,

Kumar

²

,

Mazumder

³

et al. 2017

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Abstract-Multi-robot networks use wireless communication to provide wide-ranging services such as aerial surveillance and unmanned delivery. However, effective coordination between multiple robots requires trust, making them particularly vulnerable to cyber-attacks. Specifically, such networks can be gravely disrupted by the Sybil attack, where even a single malicious robot can spoof a large number of fake clients. This paper proposes a new solution to defend against the Sybil attack, without requiring expensive cryptographic key-distribution. Our core contribution is a novel algorithm implemented on commercial Wi-Fi radios that can "sense" spoofers using the physics of wireless signals. We derive theoretical guarantees on how this algorithm bounds the impact of the Sybil Attack on a broad class of robotic coverage problems. We experimentally validate our claims using a team of AscTec quadrotor servers and iRobot Create ground clients, and demonstrate spoofer detection rates over 96%.

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“…Mostly originating from biological inspiration [2][3][4], the mathematical modeling and control of these "swarms" have advanced to tackle a multitude of problems, such as flocking [5][6][7][8][9][10], formation flight [11], area coverage [12][13][14][15], and even hostile interactions with other swarms [16]. This paper discusses a hybrid procedure for flocking and area coverage.…”

Section: Introductionmentioning

confidence: 99%

“…Controlled distribution of agents over a wide area (called "coverage control") is studied by Cortes et al [12][13][14]. The majority of these approaches analyze static convex regions.…”

Section: Introductionmentioning

confidence: 99%

Robust Region Tracking for Swarms via a Novel Utilization of Sliding Mode Control

Bacon¹,

Olgaç

²

,

Cepeda-Gomez³

2012

ICA

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Control of multi-agent autonomous swarms is studied for targeted flocking exercises. The desired decentralized control takes into account robustness against modeling uncertainties as well as bounded unknown forces. In this analysis, we consider the task of driving multiple agents to a moving "target region", as inter-agent repulsive forces help spread out the agents within the region. An unconventional form of sliding mode control is implemented to provide the robust attraction towards the region's center. For robustness a finite "boundary layer" is conceived, which corresponds to the desired target region. The flocking control forces are intentionally softened inside this target region, allowing agents to create a uniformly spaced formation guided by the inter-agent repulsion forces. Examples are given for moving circular and elliptical regions which illustrate the effectiveness of the proposed strategy.

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Coverage Control for Mobile Sensing Networks

Cited by 2,187 publications

References 55 publications

Guaranteeing Spoof-Resilient Multi-Robot Networks

Guaranteeing Spoof-Resilient Multi-Robot Networks

Guaranteeing spoof-resilient multi-robot networks

Robust Region Tracking for Swarms via a Novel Utilization of Sliding Mode Control

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