Reinforcement Learning on Reconfigurable Hardware: Overcoming Material Variability in Laser Material Processing
Ensuring consistent processing quality is challenging in laser processes due to varying material properties and surface conditions. Although some approaches have shown promise in solving this problem via automation, they often rely on predetermined targets or are limited to simulated environments. T