Buzz: An Extensible Programming Language for Self-Organizing Heterogeneous Robot Swarms
This addresses the challenge of efficiently programming and coordinating diverse robot swarms for applications like search and rescue or environmental monitoring, representing a domain-specific advancement.
The authors tackled the problem of programming heterogeneous robot swarms by introducing Buzz, a novel language that enables decentralized self-organization through compositional primitives for single-robot and swarm-level behaviors, resulting in demonstrated scalability and robustness in simulated experiments.
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.