Solving Coverage Problems with Embedded Graph Grammars

McNew, John-Michael; Klavins, Eric; Egerstedt, Magnus

doi:10.1007/978-3-540-71493-4_33

Cited by 20 publications

(21 citation statements)

References 9 publications

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“…Hybrid system theory (HST) offers an alternative, where the system can be represented by both discrete and continuous states. HST has been used in the context of swarm robotics, multirobot systems, and other multi-agent systems (Tomlin et al 1998;Fierro et al 2001;McNew and Klavins 2006;McNew et al 2007;Zavlanos et al 2009;Mesquita 2010;Mesquita and Hespanha 2012). Belta et al (2007), for example, use HST in a motion planning problem.…”

Section: Formal Methods In Swarm Roboticsmentioning

confidence: 99%

“…Its sensory input-which other robots are perceived-is used to select the controller to be executed. In McNew and Klavins (2006);McNew et al (2007), HST is used for the problem of organising the robots into subgroups while maintaining the overall connectivity. The formal properties are guaranteed by the use of embedded graph grammars.…”

Section: Formal Methods In Swarm Roboticsmentioning

confidence: 99%

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Supervisory control theory applied to swarm robotics

et al. 2016

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Currently, the control software of swarm robotics systems is created by ad hoc development. This makes it hard to deploy these systems in real-world scenarios. In particular, it is difficult to maintain, analyse, or verify the systems. Formal methods can contribute to overcome these problems. However, they usually do not guarantee that the implementation matches the specification, because the system's control code is typically generated manually. Also, there is cultural resistance to apply formal methods; they may be perceived as an additional step that does not add value to the final product. To address these problems, we propose supervisory control theory for the domain of swarm robotics. The advantages of supervisory control theory, and its associated tools, are a reduction in the amount of ad hoc development, the automatic generation of control code from modelled specifications, proofs of properties over generated control code, and the reusability of formally designed controllers between different robotic platforms. These advantages are demonstrated in four case studies using the e-puck and Kilobot robot platforms. Experiments with up to 600 physical robots Intell (2016) 10:65-97 are reported, which show that supervisory control theory can be used to formally develop state-of-the-art solutions to a range of problems in swarm robotics.

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Section: Formal Methods In Swarm Roboticsmentioning

confidence: 99%

Section: Formal Methods In Swarm Roboticsmentioning

confidence: 99%

Supervisory control theory applied to swarm robotics

et al. 2016

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“…A number of algorithms that satisfy these four constraints have been proposed and they have been used successfully for achieving and maintaining formations [15]- [18], for covering areas [19]- [21], for securing and tracking boundary curves [22]- [24], or for mimicking biological social behaviors such as flocking and swarming [25]- [28]. In this overview, we illustrate some of the common features and unifying assumptions behind this body of work.…”

Section: Introductionmentioning

confidence: 99%

Coordinated Control of Multi-Robot Systems: A Survey

Cortés

Egerstedt

2017

SICE Journal of Control, Measurement, and System Integration

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138

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: Recently, significant gains have been made in our understanding of multi-robot systems, and such systems have been deployed in domains as diverse as precision agriculture, flexible manufacturing, environmental monitoring, search-and-rescue operations, and even swarming robotic toys. What has enabled these developments is a combination of technological advances in performance, price, and scale of the platforms themselves, and a new understanding of how the robots should be organized algorithmically. In this paper, we focus on the latter of these advances, with particular emphasis on decentralized control and coordination strategies as they pertain to multi-robot systems. The paper discusses a class of problems related to the assembly of preferable geometric shapes in a decentralized manner through the formulation of descent-based algorithms defined with respect to team-level performance costs.

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“…Over the past decade, a significant amount of effort has been spent researching the latter. As a result, controllers now exist which drive teams of autonomous agents to carry out tasks such as reaching consensus (e.g., [1], [2], [3], [4]), achieving formations (e.g., [5], [6], [7]), providing sensor coverage (e.g., [8], [9], [10]), and so on. However, recent advancements in the standardization of agent-based software frameworks (e.g., [11], [12], [13]), has given rise to "heterogeneous" systems comprising of agents with different capabilities (e.g., legged robots, UAVs, AUVs, sensor nodes).…”

Section: Introductionmentioning

confidence: 99%

A measure of heterogeneity in multi-agent systems

Twu

Mostofi

Egerstedt

2014

2014 American Control Conference

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Abstract-Heterogeneous multi-agent systems have previously been studied and deployed to solve a number of different tasks. Despite this, we still lack a basic understanding of just what "heterogeneity" really is. For example, what makes one team of agents more heterogeneous than another? In this paper, we address this issue by proposing a measure of heterogeneity. This measure takes both the complexity and disparity of a system into account by combining different notions of entropy. The result is a formulation that is both easily computable and makes intuitive sense. An overview is given of existing metrics for diversity found in various fields such as biology, economics, as well as robotics, followed by a discussion of their relative merits and demerits. We show how our proposed measure of heterogeneity overcomes problematic issues identified across the previous metrics. Finally, we discuss how to apply the new measure of heterogeneity specifically to multi-agent systems by using the notion of a common task-space to compare agents with different capabilities.

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Solving Coverage Problems with Embedded Graph Grammars

Cited by 20 publications

References 9 publications

Supervisory control theory applied to swarm robotics

Supervisory control theory applied to swarm robotics

Coordinated Control of Multi-Robot Systems: A Survey

A measure of heterogeneity in multi-agent systems

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