Emergent properties of constrained active particle chains

Active collective systems are composed of many individuals that possess the ability to cooperatively change their group shape and motion. Synthetic systems with these properties can be useful for addressing functional applications or elucidating guiding principles in natural collectives. The design and use of these robotic systems requires understanding of the ways that the constraints of individuals affect the functional performance of the collective. We investigate how simple steric interaction rules between active individuals produce a versatile active system with promising functionality, by studying a chain of forward-propelled particles that can be defined by its internal geometric interaction constraints. A variety of emergent properties arise from this dynamic system, including directed movement, interactions with obstacles, and transport of loads. Modifying the geometric constraints between the active chain components provides a rich range of these observed behaviours. The resulting low- and high-level emergent properties are evaluated using an agent-based model, with a focus on understanding how the geometric constraints and relationships between interacting individuals control the collective behaviours.