Convergence-Preserving Switching for Topology-Dependent Decentralized Systems

Shucker, Brian; Murphey, Todd D.; Bennett, John K.

doi:10.1109/tro.2008.2007940

Cited by 49 publications

(40 citation statements)

References 26 publications

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“…Each type of interaction has different characteristics and gives rise to slightly different patterns. Additional theoretical work is presented in a subsequent paper (Shucker et al 2008). Flocchini et al (2008) focused on a theoretical analysis of pattern formation.…”

Section: Pattern Formationmentioning

confidence: 99%

Swarm robotics: a review from the swarm engineering perspective

et al. 2013

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Swarm robotics is an approach to collective robotics that takes inspiration from the self-organized behaviors of social animals. Through simple rules and local interactions, swarm robotics aims at designing robust, scalable, and flexible collective behaviors for the coordination of large numbers of robots. In this paper, we analyze the literature from the point of view of swarm engineering: we focus mainly on ideas and concepts that contribute to the advancement of swarm robotics as an engineering field and that could be relevant to tackle real-world applications. Swarm engineering is an emerging discipline that aims at defining systematic and well founded procedures for modeling, designing, realizing, verifying, validating, operating, and maintaining a swarm robotics system. We propose two taxonomies: in the first taxonomy, we classify works that deal with design and analysis methods; in the second taxonomy, we classify works according to the collective behavior studied. We conclude with a discussion of the current limits of swarm robotics as an engineering discipline and with suggestions for future research directions.

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Section: Pattern Formationmentioning

confidence: 99%

Swarm robotics: a review from the swarm engineering perspective

et al. 2013

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“…where 4 We refer the reader to our further work on this model [24], and related switched models of interaction [25]. with collision avoidance set Ω i = {j ∈ V | x ij ≤ ρ 0 }.…”

Section: A Connectivity Maximizing Constraint-aware Mobilitymentioning

confidence: 99%

Locally constrained connectivity control in mobile robot networks

Williams

Sukhatme

2013

2013 IEEE International Conference on Robotics and Automation

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Abstract-In this paper, we consider the problem of controlling the connectivity of a network of mobile agents under local topology constraints and proximity-limited communication. The inverse iteration algorithm for spectral analysis is formulated in a distributed manner to allow each agent to estimate a component of global network connectivity, improving on the convergence rate issues of previous approaches. Potential-based controls drive the agents to maximize connectivity under local degree constraints, maintain established links to guarantee connectivity, and avoid collisions. To achieve constraint satisfaction we propose a switched model of interaction that regulates link addition through symmetric, repulsive potentials between constraint violators, enforcing discernment in communication through spatial organization. Simulations of connectivity estimation as well as agent aggregation and leader-following applications demonstrate the ability of our proposed methods to generate connectivity maximizing, constraint-aware self organization. I. INTRODUCTIONIntense interest has been focused recently on the analysis and control of networked systems, and particularly on distributed systems of mobile agents. Such systems provide significant gains in efficiency, scalability, and robustness when compared to classical centralized solutions. Applications of mobile agent networks are multi-disciplinary and highly varied; examples include formation control [1], adaptive sampling [2], and target tracking [3].In this work we are concerned with the connectivity property of networks under proximity-limited communication and the topological dynamics induced by mobile agents. Network topology has been shown to have a profound impact on the performance and robustness of networked algorithms, for example in the analysis of formation stability [4], consensus seeking [5], and swarming behaviors [6]. Considering for example the consensus problem, it is demonstrated in [5] that topology fundamentally impacts the convergence and robustness of consensus, yielding distinct tradeoffs in connectivity and network design. These conclusions are further reflected in works such as [7], with biological insight [8]. It is then natural to consider controlling network topology to yield performance gains in networked processes like consensus, or to otherwise shape network information flow [4]. Note that connectivity (topology) control differs sharply from works that seek enhancements to the consensus algorithm itself, e.g. [9], [10]; such algorithms continue to perform at the mercy of network topology.Connectivity control has been addressed in recent works by considering various connectivity measures together with both distributed and centralized control schemes. In [11] marketbased auctions and a local connectivity measure yield hybrid

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“…Recently, environmental protection has become an urgent task and researchers have created various useful and capable coverage algorithms, including deterministic annealing [1], virtual springs [2], Smoothed Particles Hydrodynamics [3], Voronoi partitions [4] and bacteria behaviour [5]. The deterministic annealing algorithm developed by kwok et al in [1] can provide coverage to the distribution of a spatiotemporal function, and its accuracy depends on obtaining the best heating and cooling cycle.…”

Section: Introductionmentioning

confidence: 99%

“…The approach is also dependent on a heavy communication scheme in which commands are flood over the network of agents. Shucker et al used mathematical equations that describe the length of springs under a force and developed a mechanism to control the distribution of agents tracking a complex diffusing target [2]. This approach required long distance communication and might not be suitable for simple robotic agents with limited hardware.…”

Section: Introductionmentioning

confidence: 99%

A novel bio-inspired distributed coverage controller for pollution monitoring

Oyekan

2011

2011 IEEE International Conference on Mechatronics and Automation

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Abstract-The Voronoi partition method can provide a coverage to an area of interest and has gained a lot of popularity when compared with other coverage schemes such as virtual springs and deterministic annealing. This paper presents the development of a novel bio-inspired algorithm that uses a behaviour based approach to solve the problem of coverage. It is shown that by combining a source seeking behaviourbacteria chemotaxis and a group foraging behaviour -flocking, it is possible to provide coverage to an area of interest and obtain results similar to that obtained by using the Voronoi partition method. Experimental results show that the novel coverage algorithm can out perform the voronoi partition method when presented with some case study scenarios.

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Convergence-Preserving Switching for Topology-Dependent Decentralized Systems

Cited by 49 publications

References 26 publications

Swarm robotics: a review from the swarm engineering perspective

Swarm robotics: a review from the swarm engineering perspective

Locally constrained connectivity control in mobile robot networks

A novel bio-inspired distributed coverage controller for pollution monitoring

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