Ergodic Dynamics for Large-Scale Distributed Robot Systems

Intelligent autonomous robotics is a promising area with many potential applications that could benefit from non-traditional models of computation. Information processing systems interfaced with the real world must deal with a continuous and uncertain environment, and must cope with interactions across a range of time-scales. Robotics problems resist existing tools and, consequently, new perspectives are needed to address these challenges. Toward that end, we describe a dynamicsbased model for computing in large-scale distributed robot systems. The proposed method employs a compositional approach, constructing robot controllers from ergodic processes. We describe application of the method to two multi-robot tasks: decentralised task allocation, and collective strategy selection.