A Survey on Swarm Intelligence Algorithms for Optimizing Path Planning

Abstract

This survey provides an exhaustive review of advances in Swarm Intelligence algorithms applied to path planning from the year 2019 to 2024. Swarm Intelligence is a field of investigation that takes its inspiration from the behavior of social animals and has evolved to now incorporate machine learning and sensor fusion to solve pathfinding problems of growing difficulty. The application of SI in dynamic and uncertain environments is still problematic, since the efficiency and adaptability of algorithms change greatly under different conditions of operation. The paper discusses how research in diverse fields like mobile robots, autonomous vehicles, and logistics synthesizes and then evaluates the efficiency, adaptability, and performance of prominent SI algorithms. It highlights the integration of SI with modern technologies like machine learning and sensor fusion, which has demonstrated enlarged capabilities in the navigation of complex and dynamic environments. This paper identifies the research gaps and proposes certain directions for future research, hence acting as a vital resource in applying SI with a view to optimizing path planning in autonomous systems.