Biologically inspired confinement of multi-robot systems

Haque, Musad; Rahmani, Amir; Egerstedt, Magnus

doi:10.1504/ijbic.2011.041145

Cited by 34 publications

(20 citation statements)

References 7 publications

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“…Early work on herding algorithms used geometric principles to identify the relative position and posture of the shepherd with respect to the flock [35]- [37], in order to first confine the flock within a well-defined spatial zone and then impose trajectory tracking on the confined flock [38], [39]. It is generally well known that these algorithms may perform poorly when a single shepherd is employed [37].…”

Section: A Overview Of the Literaturementioning

confidence: 99%

Robotic Herding of a Flock of Birds Using an Unmanned Aerial Vehicle

et al. 2018

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Abstract-In this paper, we derive an algorithm for enabling a single robotic unmanned aerial vehicle to herd a flock of birds away from a designated volume of space, such as the air space around an airport. The herding algorithm, referred to as the mwaypoint algorithm, is designed using a dynamic model of bird flocking based on Reynolds' rules. We derive bounds on its performance using a combination of reduced-order modeling of the flock's motion, heuristics, and rigorous analysis. A unique contribution of the paper is the experimental demonstration of several facets of the herding algorithm on flocks of live birds reacting to a robotic pursuer. The experiments allow us to estimate several parameters of the flocking model, and especially the interaction between the pursuer and the flock. The herding algorithm is also demonstrated using numerical simulations.

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Section: A Overview Of the Literaturementioning

confidence: 99%

Robotic Herding of a Flock of Birds Using an Unmanned Aerial Vehicle

et al. 2018

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“…Using (23), the Lyapunov function can be simplified. Using (23), the Lyapunov function can be simplified.…”

Section: Backstepping Controllermentioning

confidence: 99%

“…Dabiri in [15] harnessed the movement flow model of a school of fish to investigate the output power efficiency of vertical axis wind turbines as opposed to the commonly used horizontal axis wind turbines. Haque et al [23] stated that the bio-inspired schemes allowed for its implementation in robotic systems and implemented foraging behaviors of bottlenose dolphins. Several other biological behaviors can be, and are being imitated for other applications.…”

Section: Introductionmentioning

confidence: 99%

Biologically Inspired Control Of A Fleet Of Uavs With Threat Evasion Strategy

ElźFerik

Thompson

2016

Asian Journal of Control

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In this paper, navigation algorithms for a fleet of multiple nonholonomic UAVs capable of evading a chasing predator and also pursuing a desired target are proposed. The proposed biologically-inspired navigation algorithms are used to define path planning trajectories which are tracked by a designed backstepping tracking controller. We implement the group of nonholonomic UAVs in an adaptive network, specifically inspired by the relationship between a school of fish and a predator. This approach approximately simulates an air combat field. To put this in context, the aim is to use a biologically inspired algorithm along with a designed controller to achieve both target pursuance and effective evasion from a predator. This is equivalent to having multiple UAVs on the same mission of attacking a target, while also aware of a predator on pursuit. The UAVs aim to maneuver and evade the predator while also coordinating their movement and behaviors in a cooperative and coherent manner.

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“…The most widely explored objective of herding is to move the flock in a certain prescribed manner, the so-called shepherding problem [20]. The literature on shepherding has generally tried to establish geometric principles for the shepherds steering the flock [21,22,23,24,25] and there have been some experimental demonstrations on ground-based robots [20,22] as well. It is generally well-known that using a single herding agent (or sheep dog) can significantly reduce the chances of success [22].…”

Section: Literature Reviewmentioning

confidence: 99%

Herding a Flock of Birds Approaching an Airport Using an Unmanned Aerial Vehicle

Gade

Paranjape

Chung

2015

AIAA Guidance, Navigation, and Control Conference

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The problem of herding a flock of birds is posed in a graph theoretic framework. A novel algorithm, called the n-wavefront algorithm, is developed for enabling a single unmanned aerial vehicle to herd a flock of birds to a desired point. The technique is applied to the problem of diverting a flock of birds approaching an airport away from a protected zone around the airport. The n-wavefront algorithm is demonstrated in simulation and compared with existing strategies using graph-based metrics.

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Biologically inspired confinement of multi-robot systems

Cited by 34 publications

References 7 publications

Robotic Herding of a Flock of Birds Using an Unmanned Aerial Vehicle

Robotic Herding of a Flock of Birds Using an Unmanned Aerial Vehicle

Biologically Inspired Control Of A Fleet Of Uavs With Threat Evasion Strategy

Herding a Flock of Birds Approaching an Airport Using an Unmanned Aerial Vehicle

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