LeRobot v0.6.1 updates include renaming lerobot.types to lerobot.lerobot_types, performance optimizations, and code refactoring. Key changes enhance documentation, policy handling, and compatibility.
This tutorial explores the challenges of deploying VLA models on embedded robotic systems, including dataset recording best practices, fine-tuning techniques for ACT and SmolVLA, and real-time performance optimization using the NXP i.MX 95 SoC. It emphasizes asynchronous inference and hardware-aware scheduling to improve control and reduce latency.
Editorial context：This guide provides hands-on best practices for deploying Vision-Language-Action (VLA) models on embedded platforms, emphasizing dataset recording, model fine-tuning, and real-time performance optimization. It highlights the importance of asynchronous inference and hardware-specific optimizations for achieving reliable robotic control.