FLASH: Efficient Visuomotor Policy via Sparse Sampling
FLASH is a generative policy that represents actions as continuous Legendre polynomials to allow for single-step inference and precise torque control. It uses sparse temporal sampling and history-anchored flow matching to achieve state-of-the-art efficiency, resulting in significantly faster inference and lower tracking errors compared to existing methods.