Perspective and Development of Brain-Inspired Swarm Navigation

Abstract

In recent years, intelligent unmanned systems such as drones, autonomous vehicles, and unmanned boats have played a significant role in various fields, including military, industrial and agricultural production, and logistics transportation. However, due to the limitations in resources and capabilities of individual intelligent unmanned systems, they are unable to meet the increasingly complex demands of real-world applications. it has become a trend to organize multiple intelligent unmanned systems into clusters to achieve collaborative work and swarm intelligence, of which swarm navigation and positioning is an important basis for swarm intelligence.Traditional satellite navigation systems are inadequate to meet the application requirements of intelligent unmanned systems in complex environments. Therefore, autonomous navigation of intelligent unmanned swarm systems has become an urgent problem to solve. Inspired by the neural mechanisms and principles of animal navigation systems and collective coordination, brain-inspired swarm navigation has emerged as a promising research field. It aims to achieve efficient and intelligent navigation in complex and unknown environments, fulfilling the navigation needs of intelligent unmanned systems operating in groups. This article provides an overview of the concept and mechanisms of brain-inspired swarm navigation. It explores the spatial neural mechanisms involved in brain-inspired swarm navigation, relevant simulation models, and swarm intelligence algorithms for brain-inspired swarm decision-making. Finally, the future directions of brain-inspired swarm navigation are discussed.

Keywords

• |brain-inspired intelligence|swarm coordination|self navigation|swarm navigation|brain-inspired navigation