摘要：AbstractTo enable high computational loads for low cost underwater drones, a cloud based architecture is proposed to take advantage of recent development in machine learning and computer vision. The processing power made available will benefit vehicles with limited onboard processing capacity. The rapid development of cloud computing services have made servers with significant computational resources easier to access. In this paper, a communication interface for cloud based multilayer architecture is proposed to enable real time performance by distributing the workload to networked processing devices. It adopts a publish-subscribe model for efficient communication between the layers. The latency and workload distribution are evaluated to assess the efficiency of the proposed method. An application to semantic segmentation of under-water scenes is also tested to measure the framework capabilities for real-time operation using more resource-demanding tools. The conducted experiments resulted in time and performance gains through offloading the underwater vehicle, and forwarding the computations to the cloud based layer.
