Galvanometric scanners are essential actuators in precision laser manufacturing, where they provide the high-speed, micrometer-scale positioning required for structuring, drilling, and additive manufacturing tasks. However, their inertial limitations give rise to tracking errors, restricting throughput and imposing constraints on both industrial and research applications. This work introduces a software-based trajectory predistortion method that directly compensates scanner dynamics without necessitating hardware upgrades, thereby offering immediate deployment across existing production environments. The proposed model-based trajectory optimization employs regularized inversion techniques combined with Butterworth filtering to generate pre-compensated command signals that counter inherent system lag and overshoot.

Experimental results highlight the effectiveness of this approach: settling times were reduced by 49.2 percent for fine 30-micrometer movements, and by 17.3 percent for larger millimeter-scale displacements. Furthermore, tracking error was halved, decreasing consistently from 200 to 100 microseconds, independent of movement amplitude. These improvements translate directly into industrial relevance. In a representative case study involving the fabrication of titanium porous transport layers for electrochemical devices, the method delivered a 38.1 percent increase in manufacturing throughput.

Because the approach is purely software-based, it requires no additional capital expenditure and integrates seamlessly into existing control architectures. Beyond the specific example demonstrated, the methodology generalizes to a wide spectrum of galvanometer-driven processes in laser micromachining, medical device manufacturing, and additive manufacturing. Broad adoption could significantly accelerate industrial productivity by unlocking latent performance in currently deployed scanner systems, avoiding costly hardware replacement and qualification efforts.