After successfully setting up your development environment and deploying your first application, you have established the foundation for working with the YNX1000 and the Autonomous Control Unit (ACU). To transition from basic setup to advanced robotic integration, you should explore the following specialized services, reference guides, and materials provided to deepen your understanding.
To build more robust and efficient applications, familiarize yourself with these core technical guides:
Once you get a handle on the basics of the platform it's time to move onto understanding more about the ACU architecture and its provided services.
The true power of the ACU lies in its ability to combine motion control with perception and intelligence. Your next step should be exploring how to utilize the YASKAWA ACU services to best benefit your application development.
The Robot Control Service (RCS) is the primary interface for managing robot operations within an ACU application. By utilizing the RCS gRPC-based API, applications can perform high-level tasks such as acquiring real-time status data, reading and writing robot variables, and executing motion commands.
The Path Planning Service (PPLS) is intended for managing robot motion in complex or dynamic environments where traditional, fixed-point programming is insufficient. By utilizing the PPLS, applications can automatically generate collision-free trajectories that account for both static obstacles and real-time environmental changes.
The AI Service on the ACU provides a streamlined way to integrate artificial intelligence without managing complex infrastructure. By using the provided gRPC-based API, your application can send data—such as images from the Machine Vision Service—to pre-configured AI models for tasks like object classification or detection.
If your project requires a bespoke solution, you can implement a custom AI container. This involves packaging your own model (e.g., a TensorRT or ONNX-optimized model) within a Docker image and ensuring your Project.json manifest sets the use_gpus resource field to true. This configuration grants your container direct access to the ACU's onboard NVIDIA GPU, enabling high-performance inference for specialized automation tasks.
| ⬅️ Previous |
|---|
| Building and Deploying Your First ACU Application |