Research on mechanical structure and collaboration of AGVs

Abstract

With the entry of intelligence and automation into our world, automated guided vehicles (AGVs) have become more and more significant in logistics, warehousing, transportation, and other industries, making transportation more convenient and fast under the system algorithm‘s command, which can save a lot of labor costs and greatly improve production efficiency. This paper mainly introduces the individual structure of AGV and the research status of the ant colony algorithm among cooperative algorithms. They determine whether AGVs can adapt to complex dynamic environments and complete tasks reliably and safely, which is a major, current concern in the AGV industry. This paper analyzes the individual structure‘s chassis, sensor technology, and navigation mode and introduces their advantages and disadvantages, application scope, working principle, etc. For the ant colony algorithm, this paper first introduces the traditional ant colony algorithm. Then it divides current improved methods into the improved methods based on the principle of ant colony algorithm and the improved methods integrated with other algorithms and compares with the traditional algorithms to introduce their improved advantages. This article aims to provide readers with a more profound comprehension of how AGVs work and their role in modern industrial automation, explain key technical points for the future, and provide directions for future research.