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:: Volume 10, Issue 3 (3-2021) ::
JGST 2021, 10(3): 201-219 Back to browse issues page
The Best Localization for Terrestrial Laser Scanner by Using Particle Swarm Optimization Algorithm
M. Heidari Mozaffar *, M. Varshosaz, M. Saadat Seresht
Abstract:   (331 Views)

For complete 3D modeling of a desired area, using by terrestrial laser scanner point cloud, it is necessary moving the set and increase the occupation points to measure the occlusions. But it takes more time and money for field measurements and in result will be increased time and calculations cost. Thus, the initial planning for selecting the optimal locations for the device in order to complete 3D model is essential and the computing field and office costs in a reasonable period decreased. In this paper, particle swarm optimization algorithm to achieve this objective has been used. In the proposed method, an approximate model of the scan region needs for the candidate deployment positions, and makes the algorithm’s search space. Each particle is set of the selected candidate points and a set of particles is considered as a groups. Cost function was considered with two goals, a reduction in occlusions and pick a least possible number of selected points. Algorithms starts with a set of multiple random selection of points, as an initial response and moving particles in the search space, during successive iterations, the algorithm answers locating the optimal laser scanner. In this process, the optimal choice system is automatic and repetitive and ensure proper alignment with the minimum number of points required for a complete measurement of region is achieved. The results show that the particle swarm optimization algorithm in a large number of the candidate can optimize the laser scanner selected points for the establishment.

Keywords: Optimal Locating, Particle Swarm Optimization, Terrestrial Laser Scanner, Occlusion
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Type of Study: Tarviji | Subject: Photo&RS
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Heidari Mozaffar M, Varshosaz M, Saadat Seresht M. The Best Localization for Terrestrial Laser Scanner by Using Particle Swarm Optimization Algorithm. JGST. 2021; 10 (3) :201-219
URL: http://jgst.issge.ir/article-1-314-en.html

Volume 10, Issue 3 (3-2021) Back to browse issues page
نشریه علمی علوم و فنون نقشه برداری Journal of Geomatics Science and Technology