Reproduce “LASER: Learning Active Sensing for Continuum Field Reconstruction” on OpenResearch

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About this paper

Huayu Deng, Jinghui Zhong, Xiangming Zhu, Yunbo Wang, Xiaokang Yang

LASER actively repositions sensors to reconstruct evolving physical fields from sparse observations. It encodes measurements into latent states, predicts future states, and uses a policy to choose sensor movements, with reconstruction error as reward. On a Navier–Stokes test with 64 sensors, its MSE was 0.169 versus 26.61 for the best heuristic, on a ×10⁻³ scale; results are simulations, not physical deployment.

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