Novel surface optimization for trajectory reconstruction in industrial robot tasks

Author:

Funes-Lora Miguel Angel1ORCID,Vega-Alvarado Eduardo2ORCID,Rivera-Blas Raúl2ORCID,Calva-Yáñez María Barbara2,Sepúlveda-Cervantes Gabriel2

Affiliation:

1. The University of Michigan, Ann Arbor, MI, USA

2. Instituto Politécnico Nacional, Ciudad de México, Mexico

Abstract

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.

Publisher

SAGE Publications

Subject

Artificial Intelligence,Computer Science Applications,Software

Reference22 articles.

1. Automated industrial robot path planning for spray painting process: A review

2. Milfelner M, Kopac J, Cus F, et al. Intelligent system for machining and optimization of 3D sculptured surfaces with ball-end milling. J Achiev Mater Manuf Eng 2006; 14.

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