2015/07/21 by Carlo Pinciroli, Adam Lee-Brown, Pinciroli, Carlo +3 · 1 voice · 30 citations
Computer Science · Engineering · #Artificial intelligence #Computer science #Database #Distributed Control Multi-Agent Systems #Distributed computing #Distributed systems and fault tolerance #Human–computer interaction #Machine learning #Marketing buzz #Modular Robots and Swarm Intelligence #Particle swarm optimization #Robot #Robustness (evolution) #Scalability #Swarm behaviour #Swarm intelligence #Swarm robotics #World Wide Web #cs.MA #cs.PL #cs.RO #cs.SE
paper · pdf · doi:10.48550/arxiv.1507.05946
published in arXiv (Cornell University) (Cornell University) · 12 pages, 4 figures, submitted to IEEE Transactions on Robotics
openalex publication_date 2015/07/21 · arxiv created 2015/08/01 · arxiv updated 2015/08/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We present Buzz, a novel programming language for heterogeneous robot swarms. Buzz advocates a compositional approach, offering primitives to define swarm behaviors both from the perspective of the single robot and of the overall swarm. Single-robot primitives include robot-specific instructions and manipulation of neighborhood data. Swarm-based primitives allow for the dynamic management of robot teams, and for sharing information globally across the swarm. Self-organization stems from the completely decentralized mechanisms upon which the Buzz run-time platform is based. The language can be extended to add new primitives (thus supporting heterogeneous robot swarms), and its run-time platform is designed to be laid on top of other frameworks, such as Robot Operating System. We showcase the capabilities of Buzz by providing code examples, and analyze scalability and robustness of the run-time platform through realistic simulated experiments with representative swarm algorithms.