Tornado method for ground point filtering from LiDAR point clouds

Mahphood, A.; Arefi, Hossein

doi:10.1016/j.asr.2020.06.030

Cited by 13 publications

(11 citation statements)

References 27 publications

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“…The main process of wheelchair/nursing-bed docking algorithm is Lidar point cloud data fitting (the point cloud is a large number of point sets expressing the spatial distribution and surface features of the target in the same spatial reference frame), local positioning and path planning [8].Besides, considering the safety and stability factors, the successful docking should meet three conditions:…”

Section: B Wheelchair /Nursing-bed Automatic Docking Methodsmentioning

confidence: 99%

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Wheelchair Automatic Docking Method for Body-Separated Nursing Bed Based on Grid Map

Zhu

Meng

et al. 2021

IEEE Access

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To improve the mode and precision of wheelchair/nursing-bed automatic docking, a novel central embedded wheelchair/nursing-bed automatic docking method based on grid map is proposed. Firstly, Laplace operator and Iterative Closest Point (ICP) algorithm are used to filter and match Lidar point cloud, and the linear features of V-shaped artificial landmark are fitted by Split-merge method and least square method. Then Extended Kalman Filter (EKF) is used to fuse Inertial Measurement Unit (IMU) and odometer data to realize the localization of the bed and wheelchair. Meanwhile, the grid map is used for path planning. Based on the center-line of the two rear wheels and the angular bisector of V-shaped artificial landmark, the wheelchair pose is adjusted in real-time to ensure that the wheelchair gradually approaches the bed along the angular bisector of V-shaped artificial landmark. The yaw angle is reduced by using the improved Proportion Integration Differentiation (PID). 9 sets of experimental data, ie. (x, y,  ) were collected at different starting positions during the docking process. The results show that the yaw angle of the wheelchair during the docking process is controlled within 2.5°, and the distance deviation between the final position and the ideal position of the wheelchair after docking is controlled within 0.02m. In the case of light interference with different luminous fluxes, the docking can still maintain good performance. The proposed docking algorithm has the robust performance of rapid response and low steady error, which can greatly improves the self-care ability of the bedridden elderly, and reduces the labor intensity of the nursing staff.

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Section: B Wheelchair /Nursing-bed Automatic Docking Methodsmentioning

confidence: 99%

“…the wheelchair adjusts its posture, turn both wheels at point D , then we can get(7) and(8).' B and ' C can be obtained from (5) (6) (7) (8).…”

mentioning

confidence: 99%

Wheelchair Automatic Docking Method for Body-Separated Nursing Bed Based on Grid Map

Zhu

Meng

et al. 2021

IEEE Access

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“…Ground point filtering is considered one of the most important challenges in building detection because the ground points have the most significant number of points. This paper uses the tornado method for this purpose (Mahphood and Arefi, 2020a). This method simulates a realistic tornado for removing objects from the ground.…”

Section: Pre-processingmentioning

confidence: 99%

Density-Based Method for Building Detection From Lidar Point Cloud

Mahphood

Arefi

2023

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. In this paper, a new building detection method based on a density of LiDAR point clouds is proposed. In this method, trees, vegetation, and any objects that have points in a vertical plane or column are removed. In the density-based method, a cube is utilized to calculate the density therein. For each point, the cube is used to determine the number of neighbouring points. The density is calculated in two cases: 3D and 2D space. In 3D space, the volumetric density is calculated using the cube. In 2D space, all points are projected onto the horizontal plane, and the surface density is calculated using a square. Next, the two densities are compared and the points with different values in both cases are removed. The method leads to promising results in the removal of vegetation and trees. Moreover, the results achieve more than 94% completeness and correctness at the per-area level.

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“…In addition to the aforementioned methods, there is an unconventional method that simulates a natural Tornado, which uses a vertical cone to remove object points located within the cone (Mahphood and Arefi, 2020a). This method has been used to obtain good results for flat areas and Type I errors.…”

Section: Introductionmentioning

confidence: 99%

Improved Tornado Method for Ground Point Filtering From Lidar Point Clouds

Mahphood

Arefi²

2023

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. In this paper, an improved Tornado method for filtering LiDAR (Light Detection and Ranging) point clouds is presented. The original method uses a vertical cone with a downward vertex and an upward base to remove the points within it as non-ground points. The remaining points are ground points. The cone moves on the ground surface over the entire region of the point cloud. In this work, the regions of the objects are predicted by extracting the vertical features that have points in the vertical plane or vertical column. Therefore, the tornado method is only used in regions that contain objects. In addition, our improved method uses a specific height for a tornado to reduce the Type I error in mountainous areas. Also, a cylinder surrounding the cone is used to reduce the distance calculations between the cone and the point cloud. The results show that this method is very effective and fast compared to the original method. It also has promising results for the Type I error. In addition, this method was tested on the International Society for Photogrammetry and Remote Sensing (ISPRS) datasets and produced outstanding results. The results show that this method achieves high filtering accuracy. Moreover, the proposed method achieves an overall average error of 6.83%, which is lower than most other methods.

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Tornado method for ground point filtering from LiDAR point clouds

Cited by 13 publications

References 27 publications

Wheelchair Automatic Docking Method for Body-Separated Nursing Bed Based on Grid Map

Wheelchair Automatic Docking Method for Body-Separated Nursing Bed Based on Grid Map

Density-Based Method for Building Detection From Lidar Point Cloud

Improved Tornado Method for Ground Point Filtering From Lidar Point Clouds

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