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Open AccessArticle

Obstacle-Aware Indoor Pathfinding Using Point Clouds

1
Applied Geotechnologies Group, Dept. Natural Resources and Environmental Engineering, University of Vigo, Campus Lagoas-Marcosende, CP 36310 Vigo, Spain
2
Faculty of Geoengineering, Mining and Geology Wroclaw University of Science and Technology, ul. Na Grobli 15, 50-421 Wroclaw, Poland
3
Department of Infrastructure Engineering, University of Melbourne, Melbourne 3010, Australia
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2019, 8(5), 233; https://doi.org/10.3390/ijgi8050233
Received: 27 April 2019 / Revised: 13 May 2019 / Accepted: 15 May 2019 / Published: 19 May 2019
(This article belongs to the Special Issue Multidimensional and Multiscale GIS)
With the rise of urban population, updated spatial information of indoor environments is needed in a growing number of applications. Navigational assistance for disabled or aged people, guidance for robots, augmented reality for gaming, and tourism or training emergency assistance units are just a few examples of the emerging applications requiring real three-dimensional (3D) spatial data of indoor scenes. This work proposes the use of point clouds for obstacle-aware indoor pathfinding. Point clouds are firstly used for reconstructing semantically rich 3D models of building structural elements in order to extract initial navigational information. Potential obstacles to navigation are classified in the point cloud and directly used to correct the path according to the mobility skills of different users. The methodology is tested in several real case studies for wheelchair and ordinary users. Experiments show that, after several iterations, paths are readapted to avoid obstacles. View Full-Text
Keywords: indoor modeling; navigation; laser scanner; point clouds; obstacle detection; evacuation routing; disabled people indoor modeling; navigation; laser scanner; point clouds; obstacle detection; evacuation routing; disabled people
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Díaz-Vilariño, L.; Boguslawski, P.; Khoshelham, K.; Lorenzo, H. Obstacle-Aware Indoor Pathfinding Using Point Clouds. ISPRS Int. J. Geo-Inf. 2019, 8, 233.

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