Swarm Robotics: From Sources of Inspiration to Domains of Application

Şahi̇n, Erol

doi:10.1007/978-3-540-30552-1_2

Cited by 619 publications

(407 citation statements)

References 24 publications

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“…Swarm robotics systems (SRSs) are composed by tens or hundreds of robots which cooperate to perform a task, without a centralized controller or global knowledge. The goal of swarm robotics is to develop systems that are robust, scalable and flexible [7].…”

Section: Introductionmentioning

confidence: 99%

Analysing Robot Swarm Decision-Making with Bio-PEPA

Massink

Brambilla

Latella

et al. 2012

Lecture Notes in Computer Science

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Abstract. We present a novel method to analyse swarm robotics systems based on Bio-PEPA. Bio-PEPA is a process algebraic language originally developed to analyse biochemical systems. Its main advantage is that it allows different kinds of analyses of a swarm robotics system starting from a single description. In general, to carry out different kinds of analysis, it is necessary to develop multiple models, raising issues of mutual consistency. With Bio-PEPA, instead, it is possible to perform stochastic simulation, fluid flow analysis and statistical model checking based on the same system specification. This reduces the complexity of the analysis and ensures consistency between analysis results. Bio-PEPA is well suited for swarm robotics systems, because it lends itself well to modelling distributed scalable systems and their space-time characteristics. We demonstrate the validity of Bio-PEPA by modelling collective decision-making in a swarm robotics system and we evaluate the result of different analyses.

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Section: Introductionmentioning

confidence: 99%

Analysing Robot Swarm Decision-Making with Bio-PEPA

Massink

Brambilla

Latella

et al. 2012

Lecture Notes in Computer Science

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“…In order to control the behavior of a group of robots, collective robotics was often inspired by the collective abilities demonstrated by social insects [3,15]. Indeed, nature has already developed many strategies that solve collective problems through the decentralized organisation and coordination of many autonomous agents by self-organized mechanisms [4].…”

Section: Introductionmentioning

confidence: 99%

Aggregation Behaviour as a Source of Collective Decision in a Group of Cockroach-Like-Robots

Garnier

Jost

Jeanson

et al. 2005

Advances in Artificial Life

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Abstract. In group-living animals, aggregation favours interactions and information exchanges between individuals, and thus allows the emergence of complex collective behaviors. In previous works, a model of a self-enhanced aggregation was deduced from experiments with the cockroach Blattella germanica. In the present work, this model was implemented in micro-robots Alice and successfully reproduced the agregation dynamics observed in a group of cockroaches. We showed that this aggregation process, based on a small set of simple behavioral rules of interaction, can be used by the group of robots to select collectively an aggregation site among two identical or different shelters. Moreover, we showed that the aggregation mechanism allows the robots as a group to "estimate" the size of each shelter during the collective decision-making process, a capacity which is not explicitly coded at the individual level.

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“…Swarms of indoor flying robots allow for efficient parallel operation and are robust due to redundancy (Sahin 2005). For tasks that employ several flying robots, spatialcoordination between robots is essential for achieving collective operation.…”

Section: Introductionmentioning

confidence: 99%

3-D relative positioning sensor for indoor flying robots

et al. 2012

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Swarms of indoor flying robots are promising for many applications, including searching tasks in collapsing buildings, or mobile surveillance and monitoring tasks in complex man-made structures. For tasks that employ several flying robots, spatial-coordination between robots is essential for achieving collective operation. However, there is a lack of on-board sensors capable of sensing the highlydynamic 3-D trajectories required for spatial-coordination of small indoor flying robots. Existing sensing methods typically utilise complex SLAM based approaches, or absolute positioning obtained from off-board tracking sensors, which is not practical for real-world operation. This paper presents an adaptable, embedded infrared based 3-D relative positioning sensor that also operates as a proximity sensor, which is designed to enable inter-robot spatial-coordination and goal-directed flight. This practical approach is robust to varying indoor environmental illumination conditions and is computationally simple.Keywords Relative positioning sensing · Indoor flying robots · Collective operation · 3D sensor · Spatial-coordination · Proximity sensing J.F.R. developed the concept of relative positioning sensing for enabling goal-directed flight on indoor collective flying robots, wrote the manuscript, developed the sensor hardware/firmware, developed the calibration tools and characterised the sensor. T.S. extensively contributed to the sensor firmware and characterisation. J.-C.Z. and D.F. conceived and directed the project sponsoring the work described in the article. They also provided continue support and feedback towards reaching the attained results.

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Swarm Robotics: From Sources of Inspiration to Domains of Application

Cited by 619 publications

References 24 publications

Analysing Robot Swarm Decision-Making with Bio-PEPA

Analysing Robot Swarm Decision-Making with Bio-PEPA

Aggregation Behaviour as a Source of Collective Decision in a Group of Cockroach-Like-Robots

3-D relative positioning sensor for indoor flying robots

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