Isaac Lab 3.0 Released: Multi-Backend Architecture for Robot Learning
v3.0.0
Isaac Lab 3.0 is now generally available, offering a unified framework for robot learning with support for multiple physics, rendering, and visualization backends. Key features include Newton physics, OV libraries, and Isaac Sim integration, along with improved simulation tools and reinforcement learning compatibility.
Isaac Lab 3.0 introduces a multi-backend architecture that supports Newton, OV, and Isaac Sim, enabling flexible physics, rendering, and visualization choices. It emphasizes unified workflows for training, evaluation, and deployment, with improved simulation capabilities and integration with reinforcement learning frameworks like RSL-RL and TorchRL.
Source: Isaac Lab — Releases · Read original article ↗
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Source：Isaac Lab — Releases · github.com