Self-Organization in Biological Systems
Self-Organization in Biological Systems
Swarm engineering
Autonomous Robots
Gathering of asynchronous robots with limited visibility
Theoretical Computer Science
Swarm robotics: from sources of inspiration to domains of application
SAB'04 Proceedings of the 2004 international conference on Swarm Robotics
SAB'04 Proceedings of the 2004 international conference on Swarm Robotics
A review of probabilistic macroscopic models for swarm robotic systems
SAB'04 Proceedings of the 2004 international conference on Swarm Robotics
Get in touch: cooperative decision making based on robot-to-robot collisions
Autonomous Agents and Multi-Agent Systems
Two different approaches to a macroscopic model of a bio-inspired robotic swarm
Robotics and Autonomous Systems
Coordination and control of multi-agent dynamic systems: models and approaches
SAB'06 Proceedings of the 2nd international conference on Swarm robotics
Property-driven design for swarm robotics
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
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We study the self-organized aggregation of a swarm of robots in a closed arena. We assume that the perceptual range of the robots are smaller than the size of the arena and the robots do not have information on the size of the swarm or the arena. Using a probabilistic aggregation behavior model inspired from studies of social insects, we propose a macroscopic model for predicting the final distribution of aggregates in terms of the parameters of the aggregation behavior, the arena size and the sensing characteristics of the robots. Specifically, we use the partition concept, developed in number theory, and its related results to build a discrete-time, non-spatial model of aggregation in swarm robotic systems under a number of simplifying assumptions. We provide simplistic simulations of self-organized aggregation using the aggregation behavior with different parameters and arena sizes. The results show that, despite the fact that the simulations did not explicitly enforce to satisfy the assumptions put forward by the macroscopic model, the final aggregate distributions predicted by the macroscopic model and obtained from simulations match.