SkyJEPA: Learning Long-Horizon World Models for Zero-Shot Sim-to-Real Control of Quadrotors
This work introduces SkyJEPA, a JEPA-style model designed for real-time quadrotor control that addresses the error amplification issues inherent in autoregressive long-horizon forecasting. The approach combines a latent dynamics model with a physics-inspired prober to map frozen latents to interpretable states, enabling physically grounded predictions.