Swarm shepherding using bearing-only measurements.

Drawing inspiration from natural herding behaviours, shepherding provides a method for swarm guidance that utilizes steering agents and can be applied in biological and robotics systems at various scales. However, while most shepherding research has relied on the precise sensing capabilities of steering agents, these assumptions do not necessarily hold in real-world tasks. To fill in the gap between practice and literature, in this study, we demonstrate that swarm shepherding can be achieved via bearing-only measurements, and explore the minimum amount of information required. We initially formulate our algorithm for a single agent and subsequently expand its application to accommodate multiple agents, incorporating strategies tailored for herding multiple swarms. Numerical simulations show the effectiveness of the algorithm under various initial placements and configurations. The minimum amount of information required by the proposed algorithm for successful shepherding, i.e. a moderate angular accuracy for the steering agents and limited communication between them, is also determined. Our proposed bearing-only algorithm offers crucial insights into swarm dynamics, which may have applications across a variety of domains, such as agriculture and search and rescue.This article is part of the theme issue 'The road forward with swarm systems'.