Overview
Cyberwave is a platform infrastructure for physical AI. It connects robots, sensors, and actuators to their digital twins and provides a unified API and SDK to standardise integration across different hardware. It enables a digital-first workflow for building, testing, and deploying physical AI systems, streamlining delivery from cloud to edge and cutting the path from prototype to production.System Architecture
| Layer | Description |
|---|---|
| Layer 1: Cyberwave Cloud | Digital twins, API / SDK, workflow orchestration, model training and deployment, observability dashboard |
| Layer 2: Cyberwave Edge | The Cyberwave stack installed on your edge compute (Raspberry Pi, Jetson, laptop). Contains the Edge Core (identity, security, device registration) and a hardware-specific driver (e.g., Cyberwave UGV Driver) that bridges Cyberwave to the physical robot. |
| Layer 3: Robot Hardware | Sensors, actuators, motor controllers, microcontrollers, and power systems |
System Components
Cyberwave Cloud
The cloud layer is the central control plane of the Cyberwave platform. It provides the interfaces, backend services, and compute infrastructure required to manage robots, digital twins, simulations, and AI models at scale.Control Plane
Control Plane
The core cloud service layer, handling identity and access management, policy enforcement, orchestration, digital twin registry, and developer interfaces for visualization, workflow management, and administrative control.
Simulation Services
Simulation Services
Cloud-scale simulation infrastructure including physics-based simulation and log replay. These services support reproducible testing and sim-to-real continuity.
Learning Services
Learning Services
Model lifecycle pipelines covering training, evaluation, validation, governance, and publishing of deployable learning artifacts. Models trained here can be deployed directly to edge nodes.
Cyberwave Edge
An edge node is a physical compute unit deployed at the periphery of the Cyberwave platform (e.g., industrial PC, embedded computer, Raspberry Pi, or similar hardware), typically co-located with one or more robots or connected devices. Edge nodes operate under strict latency, bandwidth, reliability, safety, and security constraints and are designed to function even under degraded or intermittent connectivity. For clarity: edge node refers to the physical host, and edge runtime refers to the software system executing on it. The edge runtime is a hybrid system:- Edge Core: a central host-level service running on the node OS. It handles identity, authentication, device registration, and coordination with the cloud backend.
- Runtime Services: a set of isolated Docker containers running modular, replaceable, and vendor-isolated services (e.g., hardware drivers, inference engines, data pipelines).
Robot Hardware
The physical layer consists of the robot’s hardware components:- Sensors: cameras, LiDAR, IMUs, encoders, and other perception devices that stream data to the edge runtime.
- Actuators: motors, servos, grippers, and other effectors that receive commands from the edge runtime.
- Microcontroller: the low-level controller (e.g., Arduino, STM32) that interfaces directly with sensors and actuators over serial, I2C, SPI, or CAN bus.