Learning
Physical AI

A Sim-to-Real VLA Pipeline with Seeed
reBot Arm and NVIDIA Isaac

19 DETAILED MODULES

Sim-to-Real FULL PIPELINE

5 CORE CHAPTERS

20+ Learning hours Intermediate Level

Physical AI & VLA Model Technical Stack

Master cutting-edge robotics learning pipelines with industry-grade software and hardware targets.

1. Real & Sim Data Collection

Gather teleoperation trajectories using Seeed reBot Arm B601-RS in physical environments and emulate dual-camera SO-ARM101 setups inside NVIDIA Isaac Sim.

2. Cosmos Transfer Scene Augmentation

Empower imitation learning policies using NVIDIA Cosmos3 Transfer video-to-video generative models with Canny edge & SAM2 segmentation control signals.

3. Isaac GR00T 1.7 Fine-Tuning

Train cross-embodiment Vision-Language-Action (VLA) models using System 2 VLM + System 1 Diffusion Transformer architecture on your custom robot dataset.

4. Jetson TensorRT Acceleration

Export ONNX graphs and compile a target-specific 7-engine TensorRT bundle on Jetson AGX Thor and Orin for real-time edge execution.