Dynamic Formation Control Using Networked Mobile Sensors and Centroidal Voronoi Tessellations

Rounds, Shelley; Chen, YangQuan

doi:10.1115/detc2009-87509

Cited by 4 publications

(3 citation statements)

References 16 publications

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“…Two important problems optimal mobile sensor trajectory planning and the accuracy effects and allocation of remote sensors are discussed in [33,34]. An economical and robust swarm system, which associates swarm intelligence with centroidal Voronoi tessellations (CVT) is constructed to achieve static and dynamic formation control [35]. In recent years, networked control systems compose a new class of control systems including definitive problems such as delays, loss of information and data process [36].…”

Section: Cyber Physical Systems (Cps) and Distributed Parameter Systementioning

confidence: 99%

Energy Informatics and Fractional Calculus

Liu

Zhang

Chen

2017

Volume 9: 13th ASME/IEEE International Conference on Mechatronic and Embedded Systems and Applications

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Energy informatics (EI) is relatively a blossoming and dynamic research area especially in today’s green manufacturing world. Using renewable energy and clean technology are the keys to a revitalization of the world manufacturing and job creation. Green manufacturing, which reduces resource use, waste and emissions and saving the energy, has become the priority for the manufacturers. Therefore, EI has come into a desirable solution. The fractional calculus (FC) is a mighty tool which can characterize the complex properties of the natural and social phenomena. In this paper, we have provided an overview on the current EI by describing current research topics and methods and then pointed out an outlook of how this new field might be evolved with FC in the coming future.

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Section: Cyber Physical Systems (Cps) and Distributed Parameter Systementioning

confidence: 99%

Energy Informatics and Fractional Calculus

Liu

Zhang

Chen

2017

Volume 9: 13th ASME/IEEE International Conference on Mechatronic and Embedded Systems and Applications

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“…Similar to [289], the authors [300] use centroidal Voronoi tessellations (CVTs) based approach on MAS-net to create the desired static and dynamic formations.…”

Section: Mobile Actuator and Sensor Networkmentioning

confidence: 99%

Distributed Navigation of Multi-Robot Systems For Sensing Coverage

Ahmad

2016

Preprint

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The decentralized control of mobile robots can also exhibit a cyclic behaviour under some physical constraints like a quantized orientation of mobile robot. We further investigate the cyclic behaviour appearing due to the quantized control of mobile robots under some conditions. Our nearest neighbour rule based approach offers a biased strategy in case of cyclic behaviour appearing in the team of mobile robots.We consider a clustering technique inside the team of mobile robots. Our decentralized control strategy calculates the similarity measure among the neighbours of a mobile robot. The team of mobile robots with the similarity measure based approach becomes efficient in achieving a fast consensus like on heading angle or velocity. We perform a rigorous mathematical analysis of our developed approach.We also develop a condition based on relaxed criteria for achieving consensus on velocity or heading angle of the mobile robots. Our validation approach is based on mathematical arguments and extensive computer simulations.

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“…As a more general alternative, Voronoi diagrams can be used to generate goal distributions of arbitrary shapes or contours (specified via a density function) as described by Bullo et al (2009), and this results in optimal coverage. Rounds and Chen (2009) implemented this method to direct a group of robots to zones of high light intensity. However, the iterative control procedure may produce jagged paths and result in slow convergence to local minima.…”

Section: Target Distribution Generationmentioning

confidence: 99%

Image and animation display with multiple mobile robots

Alonso–Mora

Breitenmoser

Rufli

et al. 2012

The International Journal of Robotics Research

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In this article we present a novel display that is created using a group of mobile robots. In contrast to traditional displays that are based on a fixed grid of pixels, such as a screen or a projection, this work describes a display in which each pixel is a mobile robot of controllable color. Pixels become mobile entities, and their positioning and motion are used to produce a novel experience. The system input is a single image or an animation created by an artist. The first stage is to generate physical goal configurations and robot colors to optimally represent the input imagery with the available number of robots. The run-time system includes goal assignment, path planning and local reciprocal collision avoidance, to guarantee smooth, fast and oscillation-free motion between images. The algorithms scale to very large robot swarms and extend to a wide range of robot kinematics. Experimental evaluation is done for two different physical swarms of size 14 and 50 differentially driven robots, and for simulations with 1,000 robot pixels.

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Dynamic Formation Control Using Networked Mobile Sensors and Centroidal Voronoi Tessellations

Cited by 4 publications

References 16 publications

Energy Informatics and Fractional Calculus

Energy Informatics and Fractional Calculus

Distributed Navigation of Multi-Robot Systems For Sensing Coverage

Image and animation display with multiple mobile robots

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