Enhanced precision in seam tracking sensors via adaptive refinement and fixed-geometry laser triangulation
Year: 2026
Type: article
Abstract: Precise and reliable seam tracking is essential for ensuring weld quality and productivity in robotic welding, especially under challenging conditions such as spatter, smoke, and arc glare. This study presents a seam tracking sensor that combines an adaptive refinement algorithm with fixed-geometry laser triangulation to achieve high-precision weld groove detection on matte surfaces (Ra ≈ 12.5 µm). The adaptive refinement algorithm effectively suppresses distortions caused by welding noise, while the fixed-geometry triangulation framework computes three-dimensional weld coordinates (X, Y, Z) using pre-defined, invariant hardware parameters, without requiring any online or runtime parameter re-adjustment, A Douglas–Peucker-based weld point extraction method, applied for the first time in seam tracking, was optimized for V-groove geometries. Real-time experiments using a Cartesian robotic platform demonstrated mean tracking errors of 0.10–0.18 mm in Y and 0.13–0.22 mm in Z across six workpiece orientations, with 95–98% of points within ± 0.2 mm of the reference trajectory across all tested orientations. The system achieved an average processing latency of 12.7 ms, enabling integration into high-speed welding operations. These results demonstrate the proposed sensor’s robustness to welding-induced disturbances and its potential to enhance seam tracking accuracy in robotic welding applications under realistic operating conditions.
Authors: Nurettin Gökhan Adar, Ali Yildiz
Institution: Bursa Technical University
Language: English
Subfield: Mechanical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,990
OpenAlex ID: W7155191966