Niklas Sandgren

Fraunhofer Chalmers Research Centre for Industrial Mathematics

Papers

Total Citations

H-Index

About

Niklas Sandgren is a leading researcher in the field of manufacturing automation, with a core focus on robotic spray painting and trajectory optimization. His work directly addresses the critical challenge of achieving high-precision, smooth paint finishes in complex industrial settings, particularly within the automotive industry. Sandgren’s major contribution is the development of algorithms that generate optimized trajectories for robotic arms, ensuring uniform coating while minimizing waste and cycle time. His most-cited paper, "Generating Optimized Trajectories for Robotic Spray Painting" (2022), has garnered 61 citations, highlighting its significant impact on both academic research and practical manufacturing processes. This work, alongside his earlier foundational study "Robot spray painting trajectory optimization" (2020, 14 citations), forms a cornerstone for modern automated painting systems. By tackling the difficulties of low-batch-size production and complex product geometries—tasks traditionally reliant on skilled human painters—Sandgren’s research is pivotal in advancing the quality, efficiency, and consistency of industrial finishing. His contributions are essential reading for engineers and researchers aiming to bridge the gap between robotic motion planning and real-world manufacturing demands.