Cascaded laser scanning towards high-resolution LiDAR

Zolfaghari, Parviz; Khodapanahandeh, Mehrdad; Ürey, Hakan; Ferhanoğlu, Onur

doi:10.1016/j.optlastec.2023.109906

Cited by 6 publications

(1 citation statement)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, 3D laser scanning technology utilizes laser ranging, which involves scanning the object to be measured with line structured light and collecting point cloud data from the surface of the object to be measured [ 1 ]. After performing a series of mathematical calculations, a three-dimensional model of the object to be measured is created from point cloud data [ 2 ]. In the field of linear structured laser scanning technology, the calibration of a 3D laser scanning system, laser strip center extraction, laser scanning path planning, and point cloud data processing is essential for enhancing the 3D scanning process in terms of both quality and speed.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Ant Colony Optimization with Sub-Population and Fuzzy Logic for 3D Laser Scanning Path Planning

Song,

Pu,

2024

Sensors

View full text Add to dashboard Cite

For the precise measurement of complex surfaces, determining the position, direction, and path of a laser sensor probe is crucial before obtaining exact measurements. Accurate surface measurement hinges on modifying the overtures of a laser sensor and planning the scan path of the point laser displacement sensor probe to optimize the alignment of its measurement velocity and accuracy. This manuscript proposes a 3D surface laser scanning path planning technique that utilizes adaptive ant colony optimization with sub-population and fuzzy logic (SFACO), which involves the consideration of the measurement point layout, probe attitude, and path planning. Firstly, this study is based on a four-coordinate measuring machine paired with a point laser displacement sensor probe. The laser scanning four-coordinate measuring instrument is used to establish a coordinate system, and the relationship between them is transformed. The readings of each axis of the object being measured under the normal measuring attitude are then reversed through the coordinate system transformation, thus resulting in the optimal measuring attitude. The nominal distance matrix, which demonstrates the significance of the optimal measuring attitude, is then created based on the readings of all the points to be measured. Subsequently, a fuzzy ACO algorithm that integrates multiple swarm adaptive and dynamic domain structures is suggested to enhance the algorithm’s performance by refining and utilizing multiple swarm adaptive and fuzzy operators. The efficacy of the algorithm is verified through experiments with 13 popular TSP benchmark datasets, thereby demonstrating the complexity of the SFACO approach. Ultimately, the path planning problem of surface 3D laser scanning measurement is addressed by employing the proposed SFACO algorithm in conjunction with a nominal distance matrix.

show abstract

Section: Introductionmentioning

confidence: 99%