Anders Ryberg

About

Anders Ryberg’s research lies at the intersection of robotics, computer vision, and industrial automation, with a particular focus on enhancing the precision of robotic welding systems. His major contribution is the development of a versatile machine vision system that corrects off-line programmed robot trajectories in real time, addressing the natural variations in weld joints caused by part tolerances and thermal distortion. This work, detailed in his most-cited paper “Stereo vision for path correction in off-line programmed robot welding” (31 citations), demonstrates how vision-based pose measurements can dramatically improve welding accuracy without manual reprogramming. Ryberg also advanced the field through his work on the PosEye system, a camera-based pose measurement tool designed for mounting on industrial robots. His papers on camera models and calibration algorithms—such as “A new Camera Model for Higher Accuracy Pose Calculations” (6 citations)—introduced novel strategies for achieving higher accuracy and faster convergence in pose calculations. While his citation counts reflect a focused, specialized impact, Ryberg’s innovations are critical for industries relying on automated welding, where even millimeter-level errors can compromise structural integrity. His research bridges the gap between theoretical computer vision and practical manufacturing, offering solutions that are both robust and deployable.

Research Focus

Key Achievements

Top Papers

1. 1
   Stereo vision for path correction in off-line programmed robot welding

   31 citations · 2010
2. 2
   Accuracy Investigation of a Vision Based System for Pose Measurements

   8 citations · 2006
3. 3
   A new Camera Model for Higher Accuracy Pose Calculations

   6 citations · 2006
4. 4
   A new Camera Model and Algorithms for higher Accuracy and better Convergence in Vision-based Pose Calculations

   4 citations · 2006

Key Collaborators

Contact & Links