Computing and intelligence are substantial requirements for the accurate performance of autonomous ground vehicles (AGVs). In this context, the use of cloud services in addition to onboard computers enhances computing and intelligence capabilities of AGVs. In addition, the vast amount of data processed in a cloud system contributes to overall performance and capabilities of the onboard system. This research study entails a qualitative analysis to gather insights on the applicability of the leading cloud service providers in AGV operations. These services include Google Cloud, Microsoft Azure, Amazon AWS, and IBM Cloud. The study begins with a brief review of AGV technical requirements that are necessary to determine the rationale for identifying the most suitable cloud service. The qualitative analysis studies and addresses the applicability of the cloud service over the proposed generalized AGV's architecture integration, performance, and manageability. Our findings conclude that a generalized AGV architecture can be supported by state-of-the-art cloud service, but there should be a clear line of separation between the primary and secondary computing needs. Moreover, our results show significant lags while using cloud services and preventing their use in real-time AGV operation.

中文翻译：

---

与自主地面车辆最先进的云服务集成能力研究

计算和智能是自动地面车辆 (AGV) 准确性能的重要要求。在这种情况下，除了车载计算机之外，还使用云服务增强了 AGV 的计算和智能能力。此外，在云系统中处理的大量数据有助于提高车载系统的整体性能和功能。这项研究需要进行定性分析，以收集有关领先云服务提供商在 AGV 运营中的适用性的见解。这些服务包括 Google Cloud、Microsoft Azure、Amazon AWS 和 IBM Cloud。该研究首先简要回顾了确定确定最合适云服务的基本原理所必需的 AGV 技术要求。定性分析研究并解决了云服务对提议的广义 AGV 架构集成、性能和可管理性的适用性。我们的研究结果得出结论，最先进的云服务可以支持通用 AGV 架构，但在主要和次要计算需求之间应该有明确的界限。此外，我们的结果显示，在使用云服务并阻止其在实时 AGV 操作中使用时存在显着滞后。