Finding the next-best scanner position for as-built modeling of piping systems

Abstract

ABSTRACT:Renovation of plant equipment of petroleum refineries or chemical factories have recently been frequent, and the demand for 3D asbuilt modelling of piping systems is increasing rapidly. Terrestrial laser scanners are used very often in the measurement for as-built modelling. However, the tangled structures of the piping systems results in complex occluded areas, and these areas must be captured from different scanner positions. For efficient and exhaustive measurement of the piping system, the scanner should be placed at optimum positions where the occluded parts of the piping system are captured as much as possible in less scans. However, this "nextbest" scanner positions are usually determined by experienced operators, and there is no guarantee that these positions fulfil the optimum condition. Therefore, this paper proposes a computer-aided method of the optimal sequential view planning for object recognition in plant piping systems using a terrestrial laser scanner. In the method, a sequence of next-best positions of a terrestrial laser scanner specialized for as-built modelling of piping systems can be found without any a priori information of piping objects. Different from the conventional approaches for the next-best-view (NBV) problem, in the proposed method, piping objects in the measured point clouds are recognized right after an every scan, local occluded spaces occupied by the unseen piping systems are then estimated, and the best scanner position can be found so as to minimize these local occluded spaces. The simulation results show that our proposed method outperforms a conventional approach in recognition accuracy, efficiency and computational time.

Multiple TLS Point Cloud Registration Based on Point Projection Images

“…the laser passes, and the unknown space. The space classification is used in some point cloud applications, such as change detections (Xiao et al, 2013) and next best view problems (Kawashima et al, 2014). To classify 3D space, the voxel is often used.…”

Optimal Placement of a Terrestrial Laser Scanner with an Emphasis on Reducing Occlusions

“…Unfortunately, very little attention has been paid to view‐planning methods for TLSs (Kawashima et al., ; Soudarissanane, ). The most recent published works are those by Blaer and Allen (), Biswas et al.…”

Autonomous Point Cloud Acquisition of Unknown Indoor Scenes

“…The most common solution is to discretize the space of study using a 3D grid. In many cases, instead of an octree model, a simple voxelization is used, in which each voxel is classified as empty, occupied, or occluded [25,26]. Another problem that arises is delimiting the study area.…”