What should a world model for agile quadrotor control actually provide? 📄 Arxiv: https://arxiv.org/pdf/2606.23444 🌐 Project: https://praty…

What should a world model for agile quadrotor control actually provide? 📄 Arxiv: https://arxiv.org/pdf/2606.23444 🌐 Project: https://pratyaksh10.github.io/skyjepa-project-page/ 💻 Code: https://github.com/arplaboratory/SkyJEPA Excited to share SkyJEPA: Learning Long-Horizon World Models for Zero-Shot Sim-to-Real Control of Quadrotors A useful quadrotor world model should provide: ✅ Accurate long-horizon prediction ✅ Interpretability ✅ Real-time inference for closed-loop control ✅ Zero-shot task generalization SkyJEPA learns dynamics in latent space, uses a physics-inspired prober to recover meaningful states, and enables real-time control in outdoor flights. 🔑 Takeaways: • Less compounding error • Smoother latent trajectories • Robustness to corrupted/noisy inputs • Generalization to unseen settings like propeller switching and payload changes • Zero-shot sim-to-real transfer without real-world fine-tuning to scenarios not seen during training such as propeller switching and payload changes. Huge thanks to my collaborators: @kevinghstz, @randall_balestr, @ylecun, and @loiannog #Robotics #Quadrotors #WorldModels #Sim2Real #JEPA #RepresentationLearning #Drones Media

Source: Yann LeCun (X) | 2026-06-23