A Macroscopic Analytical Model of Collaboration in Distributed Robotic Systems

Lerman, Kristina; Galstyan, Aram; Martinoli, Alcherio; Ijspeert, Auke Jan

doi:10.1162/106454601317297013

Cited by 112 publications

(117 citation statements)

References 25 publications

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“…In their seminal work, Martinoli et al (1999) used rate equations to model a clustering task where robots gather objects. Lerman et al (2001) and Martinoli et al (2004) used rate equations to model the stick pulling experiment, a task where two robots need to cooperate in order to pull sticks out of their holes. Lerman and Galstyan (2002) modeled the foraging task under the effect of interference.…”

Section: Macroscopic Modelsmentioning

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: Macroscopic Modelsmentioning

confidence: 99%

Swarm robotics: a review from the swarm engineering perspective

et al. 2013

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“…The Rate Equation formalism can be derived from theory of stochastic processes [8], although in practice, the equations are usually phenomenological and can be easily written down by considering details of the individual robot controller. The Rate Equation approach has been applied to study several distributed robot systems [14,10,7,11,1]. Below we review the elements of the mathematical formalism and illustrate with a few sample results from the robotics domain.…”

Section: Visionmentioning

confidence: 99%

“…To facilitate the analysis, we begin by drawing the macroscopic state diagram of the system. The collective behavior of the swarm is captured by an FSA that is functionally identical to the individual robot FSA, except that each state of the automaton now represents the number of robots executing that action [10,7,11]. Not every microscopic robot behavior need to become a macroscopic state.…”

Section: A Recipe For Model Constructionmentioning

confidence: 99%

A Review of Probabilistic Macroscopic Models for Swarm Robotic Systems

Lerman¹,

Martinoli

Galstyan³

2005

Lecture Notes in Computer Science

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125

106

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Abstract. In this paper, we review methods used for macroscopic modeling and analyzing collective behavior of swarm robotic systems. Although the behavior of an individual robot in a swarm is often characterized by an important stochastic component, the collective behavior of swarms is statistically predictable and has often a simple probabilistic description. Indeed, we show that a class of mathematical models that describe the dynamics of collective behavior can be generated using the individual robot controller as modeling blueprint. We illustrate the macroscopic modelling methods with the help of a few sample results gathered in distributed manipulation experiments (collaborative stick pulling, foraging, aggregation). We compare the models' predictions to results of probabilistic numeric and sensor-based simulations as well as experiments with real robots. Depending on the assumptions, the metric used, and the complexity of the models, we show that it is possible to achieve quantitatively correct predictions. VisionSwarm Robotics is an emerging area in collective robotics which uses a fully distributed control paradigm and relatively simple robots to achieve coordinated behavior at the group level. Swarm robotic systems are self-organizing, meaning that constructive collective (or macroscopic) behavior emerges from individual (or microscopic) decisions robots make. These decisions are based on purely local information that comes from other robots as well as the environment. Swarm Robotics takes its inspiration from examples of collective behavior exhibited by biological systems, such as social insects [3], and the swarming, flocking, herding, and shoaling phenomena in vertebrates. In all these systems, the abilities of the collective appear to transcend the abilities of the constituent individuals.The main advantages of the application of the swarm approach to the control of a group of robots are: (i) scalability: the control architecture can be kept exactly the same from a few units to thousands of units; (ii) flexibility: units can be dynamically added or removed, they can be given the ability to reallocate

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“…On demande à des robots de sortir des bâtons de trous où ils sont logés (Lerman et al, 2001). La présence et la collaboration de deux robots sont nécessaires pour sortir un bâton d'un trou.…”

Section: Modéliser Les Dynamiques Agrégées Des Systèmes D'agentsunclassified

De l'équation mathématique au programme informatique, dialogue entre mathématiciens et informaticiens

Treuil¹,

Lobry

Millier³

et al. 2007

Natures Sciences Sociétés

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Résumé -L'essor de l'informatique réactive les débats sur la nature des activités de modélisation et de simulation. Ce forum réunit des mathématiciens et des informaticiens à propos de la place respective des mathématiques et de l'informatique dans les modèles. La première partie propose deux exemples d'implication des mathématiques dans les sciences de la vie, et traite ensuite de la distinction entre deux formes de modélisation d'une même réalité, par une mise en équation ou une mise en programme, en soulignant la nécessité de théoriser les modèles informatiques. La seconde partie présente les apports complémentaires, à trois niveaux, des mathématiques et de l'informatique dans le cas des modèles à base d'agents. Le débat à plusieurs voix revient ensuite sur le choix du type de modélisation face au problème posé, les différences entre équations et programmes, les vérités issues des théorèmes ou des simulations, le rôle de l'expérimentation. Keywords:modeling; simulation; mathematics; informatics; agents Abstract -From mathematical equation to computational program. Dialogues between mathematicians and computer scientists. The improvement of computer capacities has promoted a very rapid development of computer sciences and re-activated debates regarding the nature of modeling and simulation activities. This forum examines the respective places of mathematics and informatics in the models. The first part proposes two cases of implication of mathematics in life sciences, then analyses the difference between two kinds of modeling of the same reality, i.e., through mathematical equations or through program building, and concludes on the need to theorize computer models. The second part deals with the complementary contributions of mathematics and computer sciences in the case of agent-based models by examining three examples. The debate involving multiple viewpoints then discusses the kind of model that is useful to answer each question, the differences between equations and programs, the differences between truth derived from theorems or from simulations, and the role of experimentation.Des notes d'actualités et des débats autour de la biométrie ont ponctué pendant 10 ans les colonnes de la revue NSS sous la plume de Jean-Marie Legay. Récemment, la revue a joué un rôle de caisse de résonance des discussions suscitées par le texte « La modélisation comme outil d'accompagnement » en permettant que s'exprime une grande variété d'opinions 1 . Ces débats sur la conception et l'utilisation des modèles sont apparemment loin d'être clos et ils concernent toutes les disciplines impliquées.

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A Macroscopic Analytical Model of Collaboration in Distributed Robotic Systems

Cited by 112 publications

References 25 publications

Swarm robotics: a review from the swarm engineering perspective

Swarm robotics: a review from the swarm engineering perspective

A Review of Probabilistic Macroscopic Models for Swarm Robotic Systems

De l'équation mathématique au programme informatique, dialogue entre mathématiciens et informaticiens

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