Searching the optimal parameters of a 3D scanner through particle swarm optimization

Braun, João; Lima, José; Pereira, Ana I.; Rocha, Cláudia; Costa, Paulo Gomes da

http://hdl.handle.net/10198/25339

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Authors

Costa, Paulo Gomes da

Abstract(s)

The recent growth in the use of 3D printers by independent users has contributed to a rise in interest in 3D scanners. Current 3D scanning solutions are commonly expensive due to the inherent complexity of the process. A previously proposed low-cost scanner disregarded uncertainties intrinsic to the system, associated with the measurements, such as angles and offsets. This work considers an approach to estimate these optimal values that minimize the error during the acquisition. The Particle Swarm Optimization algorithm was used to obtain the parameters to optimally fit the final point cloud to the surfaces. Three tests were performed where the Particle Swarm Optimization successfully converged to zero, generating the optimal parameters, validating the proposed methodology.

Keywords

Nonlinear optimization Particle swam optimization 3D scan IR sensor

URI

http://hdl.handle.net/10198/25339

Citation

Braun, João; Lima, José; Pereira, Ana I.; Rocha, Cláudia; Costa, Paulo (2021). Searching the optimal parameters of a 3D scanner through particle swarm optimization. In Pereira, Ana I.; Fernandes, Florbela P.; Coelho, João Paulo; Teixeira, João Paulo; Pacheco, Maria F.; Alves, Paulo; Lopes, Rui Pedro (Eds.) Optimization, learning algorithms and applications: first International Conference, OL2A 2021. Cham: Springer Nature. p. 138-152. ISBN 978-3-030-91884-2