Robot RL trained on photorealistic Gaussian splats transfers zero-shot
lukas_m_ziegler · x · 2026-07-21
FlexionAI says it has built a robotics RL pipeline that uses real-world site scans and photorealistic Gaussian splats to close the sim-to-real gap.
- The team argues that prior robot RL mostly relied on synthetic, untextured environments and depth images because RGB was hard to use in simulation.
- With partners Niantic Spatial and NVIDIA Robotics, they scan a real deployment site with off-the-shelf hardware, reconstruct it into a photorealistic Gaussian-splat scene, and train policies at scale in a Gym-like environment.
- Those policies then transfer zero-shot to the real robot and the environments they were trained for.
- The claim is that this should make deployment faster and policies more capable and robust, with applications beyond navigation.
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