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. Swarm 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 In Swarm Robotics Workshop: State-of-the-art Survey, Edited by E.
A review of macroscopic modelling in swarm robotics can be found in REF .
A review of probabilistic macroscopic models for swarm robotic systems
Swarm Robotics Workshop: State-of-the-art Survey, number 3342 in LNCS
Computer Science