Multisensor data fusion in dimensional metrology

By A. Weckenmann, X. Jiang, K. Sommer, U. Neuschaefer-Rube, J. Seewig, L. Shaw, T. Estler. 2009

296 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Mechanical Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/7ef1bcbfae2cebaf28ff34b01026b9d212e3b75a

Citations in the corpus

• A review of interferometry for geometric measurement (2018, unknown): “Since the demands of the complexity and accuracy of dimensional and surface metrology are ever-growing, multi-sensor data fusion methods are proposed to obtain holistic information and improve the reliability or reduce the uncertainty of measurement data [248].”
• On-machine and in-process surface metrology for precision manufacturing (2019, unknown): “The best fit of this discrete model to the set of measured points needs segmentation [202], registration of 3D point clouds [237] and alignment methods [37].”