Novel surface optimization for trajectory reconstruction in industrial robot tasks

Miguel Angel Funes-Lora, Eduardo Vega-Alvarado, Raúl Rivera-Blas, María Barbara Calva-Yáñez, Gabriel Sepúlveda-Cervantes

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

2 Citas (Scopus)

Resumen

This study presents a novel algorithm implementation that optimizes manually recorded toolpaths with the use of a 3D-workpiece model to reduce manual error induced. The novel algorithm has three steps: workpiece declaration, manual toolpath declaration, and toolpath optimization using steepest descent algorithm. Steepest descent finds the surface route wherein the manually recorded toolpaths traverse over a 3D-workpiece surface. The optimized toolpaths were simulated and tested with an industrial robot showing minimal error compared to the desired optimized toolpaths. The results obtained from the presented implementation on three different trajectories demonstrate that the proposed methodology can reduce the manual error induced using as a reference the CAD-workpiece surface.

Idioma originalInglés
PublicaciónInternational Journal of Advanced Robotic Systems
Volumen18
N.º6
DOI
EstadoPublicada - 14 dic. 2021

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