The underlying framework for controlling autonomous robots and complex automation applications are Operating Systems (OS) capable of scheduling perception-and-control tasks, as well as providing real-time data communication to other robotic peers and remote cloud computers. In this paper, we introduce CyberCortex AI, a robotics OS designed to enable heterogeneous AI-based robotics and complex automation applications. CyberCortex AI is a decentralized distributed OS which enables robots to talk to each other, as well as to High Performance Computers (HPC) in the cloud. Sensory and control data from the robots is streamed towards HPC systems with the purpose of training AI algorithms, which are afterwards deployed on the robots. Each functionality of a robot (e.g. sensory data acquisition, path planning, motion control, etc.) is executed within a so-called DataBlock of Filters shared through the internet, where each filter is computed either locally on the robot itself, or remotely on a different robotic system. The data is stored and accessed via a so-called Temporal Addressable Memory (TAM), which acts as a gateway between each filter's input and output. CyberCortex.AI has two main components: i) the CyberCortex AI inference system, which is a real-time implementation of the DataBlock running on the robots' embedded hardware, and ii) the CyberCortex AI dojo, which runs on an HPC computer in the cloud, and it is used to design, train and deploy AI algorithms. We present a quantitative and qualitative performance analysis of the proposed approach using two collaborative robotics applications: i) a forest fires prevention system based on an Unitree A1 legged robot and an Anafi Parrot 4K drone, as well as ii) an autonomous driving system which uses CyberCortex.AI for collaborative perception and motion control.

翻译：控制自主机器人与复杂自动化应用的基础框架是能够调度感知-控制任务、并为其他机器人节点及远程云端计算机提供实时数据通信的操作系统。本文介绍CyberCortex AI，一种专为异构化人工智能机器人及复杂自动化应用设计的机器人操作系统。CyberCortex AI是一种去中心化分布式操作系统，使机器人能够相互通信，并与云端的高性能计算系统进行交互。来自机器人的传感与控制数据流被传输至高性能计算系统，用于训练人工智能算法，训练完成的算法随后部署于机器人之上。机器人的每项功能（例如传感数据采集、路径规划、运动控制等）均在一种通过互联网共享的、称为“过滤器数据块”的模块中执行，其中每个过滤器可在机器人本地计算，亦可在其他机器人系统上远程计算。数据通过一种称为“时序可寻址存储器”的机制进行存储与访问，该存储器充当各过滤器输入与输出间的网关。CyberCortex.AI包含两大核心组件：i) CyberCortex AI推理系统，这是在机器人嵌入式硬件上实时运行的数据块实现；ii) CyberCortex AI训练平台，该平台运行于云端高性能计算机，用于设计、训练和部署人工智能算法。我们通过两项协同机器人应用对所提方法进行定量与定性性能分析：i) 基于Unitree A1四足机器人与Anafi Parrot 4K无人机的森林火灾预防系统；ii) 利用CyberCortex.AI实现协同感知与运动控制的自动驾驶系统。