Introduction

Kagan, Eugene; Shvalb, Nir; Ben‐Gal, Irad

doi:10.1002/9781119213154.ch0

Cited by 2 publications

(3 citation statements)

References 35 publications

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“…Similar self-organization phenomena occur in self-propelled, active-matter systems 12 – 16 . Both theoretical and applied research has focused on understanding the principles underlying collective motion 1 , 2 , 17 – 24 , and how such principles can be instantiated in mobile-robotic systems 25 – 29 . Applications for the latter range from mapping 30 , to exploration 27 , and resource allocation 31 – 33 .…”

Section: Introductionmentioning

confidence: 99%

“…Agent interactions in both natural and decentralized robotic swarms are typically sparse and local due to finite bandwidth and communication range 29 , 34 , 35 . Sparse and heterogeneous network effects on swarming are understood analytically, mostly within the context of controlling teams of mobile agents through decentralized, average consensus algorithms 20 , 36 – 38 .…”

Section: Introductionmentioning

confidence: 99%

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Swarm shedding in networks of self-propelled agents

Hindes

Edwards

Kasraie

et al. 2021

Sci Rep

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Understanding swarm pattern formation is of great interest because it occurs naturally in many physical and biological systems, and has artificial applications in robotics. In both natural and engineered swarms, agent communication is typically local and sparse. This is because, over a limited sensing or communication range, the number of interactions an agent has is much smaller than the total possible number. A central question for self-organizing swarms interacting through sparse networks is whether or not collective motion states can emerge where all agents have coherent and stable dynamics. In this work we introduce the phenomenon of swarm shedding in which weakly-connected agents are ejected from stable milling patterns in self-propelled swarming networks with finite-range interactions. We show that swarm shedding can be localized around a few agents, or delocalized, and entail a simultaneous ejection of all agents in a network. Despite the complexity of milling motion in complex networks, we successfully build mean-field theory that accurately predicts both milling state dynamics and shedding transitions. The latter are described in terms of saddle-node bifurcations that depend on the range of communication, the inter-agent interaction strength, and the network topology.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Swarm shedding in networks of self-propelled agents

Hindes

Edwards

Kasraie

et al. 2021

Sci Rep

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“…Solutions for those problems require robust and frequently updated spatial information about surroundings. For real-life applications of such systems, one should allow for temporary outages of a sensor (in case of an e.g., hardware fail) or temporary lack of data of satisfactory quality (e.g., weak, severely affected by multipath GNSS signal in a dense urban environment [ 4 ]). Numerous data fusion algorithms have been proposed to both prevent an autonomous mission from total failure in described cases and to increase the reliability and accuracy of position estimation [ 5 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

Accuracy Evaluation of Selected Mobile Inspection Robot Localization Techniques in a GNSS-Denied Environment

Szrek

Trybała

Góralczyk

et al. 2020

Sensors

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Locating an inspection robot is an essential task for inspection missions and spatial data acquisition. Giving a spatial reference to measurements, especially those concerning environmental parameters, e.g., gas concentrations may make them more valuable by enabling more insightful analyses. Thus, an accurate estimation of sensor position and orientation is a significant topic in mobile measurement systems used in robotics, remote sensing, or autonomous vehicles. Those systems often work in urban or underground conditions, which are lowering or disabling the possibility of using Global Navigation Satellite Systems (GNSS) for this purpose. Alternative solutions vary significantly in sensor configuration requirements, positioning accuracy, and computational complexity. The selection of the optimal solution is difficult. The focus here is put on the assessment, using the criterion of the positioning accuracy of the mobile robot with no use of GNSS signals. Automated geodetic surveying equipment is utilized for acquiring precise ground truth data of the robot’s movement. The results obtained, with the use of several methods, compared: Wheel odometry, inertial measurement-based dead-reckoning, visual odometry, and trilateration of ultra-wideband signals. The suitability, pros, and cons of each method are discussed in the context of their application in autonomous robotic systems, operating in an underground mine environment.

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Introduction

Cited by 2 publications

References 35 publications

Swarm shedding in networks of self-propelled agents

Swarm shedding in networks of self-propelled agents

Accuracy Evaluation of Selected Mobile Inspection Robot Localization Techniques in a GNSS-Denied Environment

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