Optimization of laser scanner positioning networks for architectural surveys through the design of genetic algorithms
In recent decades, the use of terrestrial laser scanners has become the principal method for metric data collection in architecture. However, there are no systematic procedures in place to plan the data capture process. This means that the obtaining tasks of the clouds of points are based either on...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Universidad de Sevilla (US) |
| Repositorio: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/170973 |
| Acceso en línea: | https://hdl.handle.net/11441/170973 https://doi.org/10.1016/j.measurement.2020.108898 |
| Access Level: | acceso abierto |
| Palabra clave: | Terrestrial laser scanner Genetic algorithm Optimization |
| Sumario: | In recent decades, the use of terrestrial laser scanners has become the principal method for metric data collection in architecture. However, there are no systematic procedures in place to plan the data capture process. This means that the obtaining tasks of the clouds of points are based either on operator experience, or on the overlap register that grants a complete acquisition. In both cases, data redundancy represents a significant percentage, which forces subsequent filtration or point removal. This work describes the design and development of an automated methodology, based on genetic algorithms, for the selection of a set of positions from which to execute the data capture process. The algorithm designed herein is applied to a variety of cases, thereby attaining the best station-positioning network for data collection, which maximizes coverage and minimizes overlap between clouds of points. |
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