Energy Efficient Swarm Deployment for Search in Unknown Environments

Stirling, Timothy; Floreano, Dario

doi:10.1007/978-3-642-15461-4_61

Cited by 16 publications

(13 citation statements)

References 7 publications

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“…These passive robots are assumed busy with other collective behaviors but are able to guide the navigating robots. Stirling and Floreano (2010) used a swarm of flying robots to achieve area coverage. In their work, the robots are deployed sequentially and each robot determines its position according to the position of the previously deployed robots.…”

Section: Collective Exploration Descriptionmentioning

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: Collective Exploration Descriptionmentioning

confidence: 99%

Swarm robotics: a review from the swarm engineering perspective

et al. 2013

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“…An extensive review of research related to the bio-inspired techniques and the most behaviour of the robots can be found in [9,27]. Regarding the energy consumption problem, researchers have approached this problem in different ways, including minimizing the weight of robots, pre-positioning energy sources into the environments, minimizing communication ranges of robots, sending data in a simple form [28], reducing the direct communication and the use of multi-hop communication links between robots [29], minimizing the distrance of the traveling path [30,31]. For example, Barca et al addressed the problems related to energy consumption in [32].…”

Section: Related Workmentioning

confidence: 99%

“…It is worth pointing out that the simulations were done by applying the same exploration strategy explained in Section 4, since the main focus of the work is to analyze the performance of the coordination techniques applied to the recruiting task. These experiments are designed to analyze the performance of the coordination strategies by varying the number of the robots in the area k={10, 15,20,25,30,35,40,45,50, 60} and the grid area with different numbers of cells in x and y dimension {40x40, 50x50, 60x60}, keeping a constant number of targets and the number of robots needed to perform a target. We have evaluated in this case the behavior of the approaches when a few or many robots are used in the area of different sizes.…”

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confidence: 99%

Comparison of bio-inspired algorithms applied to the coordination of mobile robots considering the energy consumption

Palmieri

Yang

Rango

et al. 2017

Neural Comput & Applic

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Many applications related to autonomous mobile robots require to explore in an unknown environment searching for static targets, without any a priori information about the environment topology and target locations. Targets in such rescue missions can be fire, mines, human victims, or dangerous material that the robots have to handle. In these scenarios, some cooperation among the robots is required for accomplishing the mission. This paper focuses on the application of different bio-inspired metaheuristics for the coordination of a swarm of mobile robots that have to explore an unknown area in order to rescue some distributed targets. This problem is formulated by first defining an optimization model and then considering two subproblems: exploration and recruiting. Firstly, the environment is incrementally explored by robots using a modified version of ant colony optimization. Then, when a robot detects a target, a recruiting mechanism is carried out to recruit more robots to carry out the disarm task together. For this purpose, we have proposed and compared three approaches based on three different bio-inspired algorithms (Firefly Algorithm, Particle Swarm Optimization and Artificial Bee Algorithm). A computational study and extensive simulations have been carried out to assess the behavior of the proposed approaches and to analyze their performance in terms of total energy consumed by the robots to complete

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“…- [26] and [27] Navigation behaviors Coordination motion -Moving in formation similarly to schools of fish or flocks of birds.…”

Section: Problem Classificationmentioning

confidence: 99%

An Overview of Swarm Robotics: Swarm Intelligence Applied to Multi-robotics

Khaldi¹,

Cherif²

2015

IJCA

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As an emergent research area by which swarm intelligence is applied to multi-robot systems; swarm robotics (a very particular and peculiar sub-area of collective robotics) studies how to coordinate large groups of relatively simple robots through the use of local rules. It focuses on studying the design of large amount of relatively simple robots, their physical bodies and their controlling behaviors. Since its introduction in 2000, several successful experimentations had been realized, and till now more projects are under investigations. This paper seeks to give an overview of this domain research; for the aim to orientate the readers, especially those who are newly coming to this research field. General TermsSwarm robotics, swarm intelligence, multi-robot systems.

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Energy Efficient Swarm Deployment for Search in Unknown Environments

Cited by 16 publications

References 7 publications

Swarm robotics: a review from the swarm engineering perspective

Swarm robotics: a review from the swarm engineering perspective

Comparison of bio-inspired algorithms applied to the coordination of mobile robots considering the energy consumption

An Overview of Swarm Robotics: Swarm Intelligence Applied to Multi-robotics

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