This design trains pose, segmentation or inspection models on AxiForge, validates them against a digital twin and production captures, then serves them on AxiOverseer while AxiGovernor supports controls integration.
Dataset and frames
Version images, depth/point clouds, annotations, camera intrinsics/extrinsics, robot/tool frames, product CAD and lighting state. Keep train/validation/test splits independent by physical scene or production period. Include negative and uncertain examples.
Simulation and training
Use the twin to generate labelled rare poses, occlusion and fault states, but randomise only physically plausible variables. Train on AxiForge with two 96GB GPUs and record seeds, image digest and data version. Compare synthetic-only, real-only and mixed training to quantify the sim-to-real gap.
Perception service
Optimise the approved model with TensorRT where appropriate and deploy behind a bounded interface on AxiOverseer. DeepStream can handle multiple video streams; ROS 2/NITROS can reduce supported copy paths. Timestamp every input/output and reject stale or uncalibrated frames.
Cell integration
AxiGovernor hosts TwinCAT engineering, ADS integration and virtual commissioning. The perception service returns class/pose/confidence; the robot/controller applies reachability, collision, interlock and safety checks. Network or AI failure leads to a defined state, not an unbounded command.
Production acceptance
Test every part family, pose, lighting condition and line rate. Measure sensor-to-decision p99 latency, dropped frames, pose error and failure recovery. Run shadow mode and supervised trials before enabling commands. Preserve the previous model for immediate rollback.
Primary technical references
- NVIDIA DeepStream documentation
- NVIDIA Isaac ROS NITROS concepts
- ROS 2 technical overview
- NVIDIA Triton Inference Server documentation
- Beckhoff TwinCAT 3 base and ADS product documentation
References are provided for software architecture and implementation planning. Validate the versions, licences, support matrix and regulated-use requirements applicable to the final deployment.
From technical concept to production system
Apply this technology through an Axiotech engineering work package
Axiotech can connect the compute, AI or analytics platform to the machine controls, data contracts, validation evidence and lifecycle-support model required for industrial use.
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