A real-time FPGA-based reinforcement learning controller, trained on the fly with the optical reflection signal as reward, adapts laser power to surface roughness and reports reward gains of up to 23% over constant-power baselines.
A review on laser processing in electronic and mems packaging,
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Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing
A real-time FPGA-based reinforcement learning controller, trained on the fly with the optical reflection signal as reward, adapts laser power to surface roughness and reports reward gains of up to 23% over constant-power baselines.