LASER: Learning Active Sensing for Continuum Field Reconstruction

ArXi:2604.19355v1 Announce Type: cross High-fidelity measurements of continuum physical fields are essential for scientific discovery and engineering design but remain challenging under sparse and constrained sensing. Conventional reconstruction methods typically rely on fixed sensor layouts, which cannot adapt to evolving physical states. We propose LASER, a unified, closed-loop framework that formulates active sensing as a Partially Observable Marko Decision Process