A novel formulation of the set cover problem is presented to find the optimal placement of the scan stations in a terrestrial laser scanning survey. The problem is formulated in 2-D by including sensor-based constraints such as coverage and overlap. The coverage constraint ensures a minimum density of horizontal scan lines on the ground. The overlap constraint enables automatic scan alignment and registration. The optimization problem takes into account both environment occlusions and a maximum allowed incidence angle of the laser beams. The adopted laser model includes fixed parameters such as laser height, angular resolution, field of view, and minimum and maximum sensor range. The sensor placement problem is solved using a numerical approach implemented on graphics processing unit (GPU). Thanks to the GPU acceleration, experiments have been performed in large-scale environments with internal structures.

Sensor-based optimization of terrestrial laser scanning measurement setup on GPU / Giorgini, M.; Marini, S.; Monica, R.; Aleotti, J.. - In: IEEE GEOSCIENCE AND REMOTE SENSING LETTERS. - ISSN 1545-598X. - 16(2019), pp. 1452-1456. [10.1109/LGRS.2019.2899681]

Sensor-based optimization of terrestrial laser scanning measurement setup on GPU

Giorgini M.;Marini S.;Monica R.;Aleotti J.
2019

Abstract

A novel formulation of the set cover problem is presented to find the optimal placement of the scan stations in a terrestrial laser scanning survey. The problem is formulated in 2-D by including sensor-based constraints such as coverage and overlap. The coverage constraint ensures a minimum density of horizontal scan lines on the ground. The overlap constraint enables automatic scan alignment and registration. The optimization problem takes into account both environment occlusions and a maximum allowed incidence angle of the laser beams. The adopted laser model includes fixed parameters such as laser height, angular resolution, field of view, and minimum and maximum sensor range. The sensor placement problem is solved using a numerical approach implemented on graphics processing unit (GPU). Thanks to the GPU acceleration, experiments have been performed in large-scale environments with internal structures.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11381/2866275
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