Contribution to a conference proceedings/Contribution to a book IMPULSE-2025-00139

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Analysis of Point Set Registration Algorithms for Industrial Parts

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2025
Springer Nature Switzerland Cham
ISBN: 978-3-031-74010-7

Annals of Scientific Society for Assembly, Handling and Industrial Robotics 2023 / Ihlenfeldt, Steffen (Editor) ; Cham : Springer Nature Switzerland, 2025, Chapter 18 ; ISBN: 978-3-031-74009-1 ; doi:10.1007/978-3-031-74010-7
Annals of Scientific Society for Assembly, Handling and Industrial Robotics 2023, ChemnitzChemnitz, Germany, 22 Jun 2023 - 23 Jun 20232023-06-222023-06-23
Cham : Springer Nature Switzerland : 1st ed. 2025, 1 Online-Ressource(VII, 318 p. 124 illus., 118 illus. in color. () [10.1007/978-3-031-74010-7_18]

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Abstract: In this paper, we investigate the suitability of existing point set registration algorithms for the task of pose estimation of industrial parts. Numerous algorithms with different characteristics have been developed already. However, no comparative analysis regarding the performance in the context of industrial parts have been conducted yet. We implement a comparative study by applying various point set registration algorithms to an industrial part and varying the point cloud density. The results of our study provide insights into the performance of different algorithms and shed light on the best practices for point set registration in the context of industrial parts.

Keyword(s): Robotics (LCSH) ; Control engineering (LCSH) ; Automation (LCSH) ; Machine learning (LCSH) ; Instrument and Method Development (1st) ; Industrial Application (2nd) ; Instrument and Method Development (2nd)

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Note: Open Access;

Contributing Institute(s):
  1. STRESSI (STRESSI)
Experiment(s):
  1. STRESS-SPEC: Materials science diffractometer (SR3)

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 Record created 2025-11-05, last modified 2025-11-06


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