scholarly journals Fast and coarse registration of point cloud in ICP three-dimensional space

2020 ◽  
Vol 1453 ◽  
pp. 012023 ◽  
Author(s):  
Xiaokang Ren ◽  
Mai Zhang ◽  
Wenqiao Wang ◽  
Xuetao Mao ◽  
Jie Ren
Keyword(s):  
Point Cloud ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Coarse Registration ◽  
Three Dimensional Space

scholarly journals TIMESTAMP OFFSET DETERMINATION BETWEEN AN ACTUATED LASER SCANNER AND ITS CORRESPONDING MOTOR

2017 ◽  
Vol IV-1/W1 ◽  
pp. 99-106 ◽  
Author(s):  
R. Voges ◽  
C. S. Wieghardt ◽  
B. Wagner
Keyword(s):  
Data Acquisition ◽  
Point Cloud ◽  
Dimensional Space ◽  
Low Cost ◽  
Three Dimensional ◽  
Laser Scanner ◽  
3D Data ◽  
Laser Scanners ◽  
Slam Algorithm ◽  
Three Dimensional Space

Motor actuated 2D laser scanners are key sensors for many robotics applications that need wide ranging but low cost 3D data. There exist many approaches on how to build a 3D laser scanner using this technique, but they often lack proper synchronization for the timestamps of the actuator and the laser scanner. However, to transform the measurement points into three-dimensional space an appropriate synchronization is mandatory. Thus, we propose two different approaches to accomplish the goal of calculating timestamp offsets between laser scanner and motor prior to and after data acquisition. Both approaches use parts of a SLAM algorithm but apply different criteria to find an appropriate solution. While the approach for offset calculation prior to data acquisition exploits the fact that the SLAM algorithm should not register motion for a stationary system, the approach for offset calculation after data acquisition evaluates the perceived clarity of a point cloud created by the SLAM algorithm. Our experiments show that both approaches yield the same results although operating independently on different data, which demonstrates that the results reflect reality with a high probability. Furthermore, our experiments exhibit the significance of a proper synchronization between laser scanner and actuator.

Introducing data analytics to the robotic drilling process

2018 ◽  
Vol 45 (3) ◽  
pp. 371-378 ◽  
Author(s):  
Toufik Al Khawli ◽  
Hamza Bendemra ◽  
Muddasar Anwar ◽  
Dewald Swart ◽  
Jorge Dias
Keyword(s):  
Point Cloud ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Data Sets ◽  
Drilling Process ◽  
Data Set ◽  
Content Type ◽  
Robotic Drilling ◽  
Geometric Primitives ◽  
Three Dimensional Space

PurposeThis paper presents a method for extracting the geometric primitives of a circle in a three-dimensional space from a discrete point cloud data set obtained by a laser stripe sensor. This paper aims to first establish a reference frame for the robotic drilling process by detecting the position and orientation of a reference hole on structural parts in a pre-drilling step, and second, to perform quality inspection of the hole in a post-drilling step.Design/methodology/approachThe method is divided into the following steps: a plane is initially fitted on the data by evaluating the principle component analysis using singular value decomposition; the data points or measurements are then rotated around an arbitrary axis using the Rodrigues’ rotation formula such that the normal direction of the estimated plane and thez-axis direction is parallel; the Delaunay triangulation is constructed on the point cloud and the confidence interval is estimated for segmenting the data set located at the circular boundary; and finally, a circular profile is fitted on the extracted set and transformed back to the original position.FindingsThe geometric estimation of the circle in three-dimensional space constitutes of the position of the center, the diameter and the orientation, which is represented by the normal vector of the plane that the circle lives in. The method is applied on both simulated data set with the addition of several noise levels and experimental data sets. The main purpose of both the tests is to quantify the accuracy of the estimated diameter. The results show good accuracy (mean relative error < 1 per cent) and high robustness to noise.Research limitations/implicationsThe proposed method is applied here to estimate the geometric primitives of only one circle (the reference hole). If multiple circles are needed, an addition clustering procedure is required to cluster the segmented data into multiple data sets. Each data set represents a circle. Also, the method does not operate efficiently on a sparse data sets. Dense data are required to cover the hole (at least ten scans to cover the hole diameter).Practical implicationsResearchers and practitioners can integrate this method with several robotic manufacturing applications where high accuracy is required. The extracted position and orientation of the hole are used to minimize the positioning and alignment errors between the mounted tool tip and the workpiece.Originality/valueThe method introduces data analytics for estimating the geometric primitives in the robotic drilling application. The main advantage of the proposed method is to register the top surface of the workpiece with respect to robot base frame with a high accuracy. An accurate workpiece registration is extremely necessary in the lateral direction (identifying where to drill), as well as in the vertical direction (identifying how far to drill).

scholarly journals On the 3D Track Planning for Electric Power Inspection Based on the Improved Ant Colony Optimization and A∗ Algorithm

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Zheng Huang ◽  
Xuefeng Zhai ◽  
Hongxing Wang ◽  
Hang Zhou ◽  
Hongwei Zhao ◽  
...  
Keyword(s):  
Ant Colony Optimization ◽  
Point Cloud ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Ant Colony ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Shortest Route ◽  
Route Length ◽  
Three Dimensional Space

At present, multirotor drones are restricted by the control accuracy and cannot position accurately according to the accuracy of point cloud data. Also, track planning in three-dimensional space is much more complicated than that in two-dimensional space, which means that existing track planning methods cannot achieve fast planning. Meanwhile, most existing researches were implemented in quasi-three-dimensional space with the shortest route length as the objective function and omitted environmental impacts. To overcome these, this paper uses the grid method to segment point cloud data of the flying space via ArcGIS software according to the drone’s controlling accuracy. It also extracts the grid coordinate information and maps it to a three-dimensional matrix to build the model accurately. This paper sets the minimal energy consumption as the objective function and builds a track planning model based on the drone’s performance and natural wind constraints. The improved ant colony optimization and A∗ (ACO-A∗) algorithm are utilized to design this algorithm for a faster solution. That is, we use the improved ant colony optimization to quickly find a near-optimal track covering all viewpoints with the minimal energy consumption. The improved A∗ algorithm will be used for local planning for adjacent tracks passing through obstacles. In the designed simulation environment, the simulation results show that, to ensure that the same components are shot, the improved algorithm in this paper can save 62.88% energy compared to that of the Shooting Manual of Drone Inspection Images for Overhead Transmission Lines. Also, it can save 9.33% energy compared to a track with the shortest route length. Besides, the ACO-A∗ algorithm saves 96.6% time than the A∗ algorithm.

scholarly journals Migration Measurement of Pins in Postoperative Recovery of the Proximal Femur Fractures Based on 3D Point Cloud Matching

Medicina ◽  
2021 ◽  
Vol 57 (5) ◽  
pp. 406 ◽  
Author(s):  
Kaifeng Liu ◽  
Kouki Nagamune ◽  
Keisuke Oe ◽  
Ryosuke Kuroda ◽  
Takahiro Niikura
Keyword(s):  
Proximal Femur ◽  
Point Cloud ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Ct Images ◽  
Postoperative Recovery ◽  
Proximal Femur Fractures ◽  
Femur Fractures ◽  
Measurement Results ◽  
Three Dimensional Space

Background and objectives: Internal fixation is one of the most effective methods for the treatment of proximal femur fractures. The migration of implants after the operation can seriously affect the reduction of treatment and even cause complications. Traditional diagnosis methods can not directly measure the extent of displacement. Methods: Based on the analysis of Hansson pins, this paper proposes a measurement method based on three-dimensional matching, which uses computerized tomography (CT) images of different periods of patients after the operation to analyze the implants’ migration in three-dimensional space with the characteristics of fast speed and intuitive results. Results and conclusions: The measurement results show that the method proposed in this paper has more minor errors, more flexible coordinate system conversion, and more explicit displacement analysis than the traditional method of manually finding references in CT images and measuring displacement.

Extension of the Spatial PDI Model to Three Dimensions

1997 ◽  
Vol 84 (1) ◽  
pp. 176-178
Author(s):  
Frank O'Brien
Keyword(s):  
Population Density ◽  
Dimensional Space ◽  
Finite Lattice ◽  
Three Dimensional ◽  
Upper Bounds ◽  
Three Dimensions ◽  
Lower And Upper Bounds ◽  
Density Index ◽  
Three Dimensional Space

The author's population density index ( PDI) model is extended to three-dimensional distributions. A derived formula is presented that allows for the calculation of the lower and upper bounds of density in three-dimensional space for any finite lattice.

A Peptoid with Extended Shape in Water

2019 ◽  
Author(s):  
Jumpei Morimoto ◽  
Yasuhiro Fukuda ◽  
Takumu Watanabe ◽  
Daisuke Kuroda ◽  
Kouhei Tsumoto ◽  
...  
Keyword(s):  
Spectroscopic Analysis ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Biomolecular Recognition ◽  
Biological Application ◽  
New Class ◽  
Proteolytic Resistance ◽  
Pharmacokinetic Properties ◽  
Optically Pure ◽  
Three Dimensional Space

<div> <div> <div> <p>“Peptoids” was proposed, over decades ago, as a term describing analogs of peptides that exhibit better physicochemical and pharmacokinetic properties than peptides. Oligo-(N-substituted glycines) (oligo-NSG) was previously proposed as a peptoid due to its high proteolytic resistance and membrane permeability. However, oligo-NSG is conformationally flexible and is difficult to achieve a defined shape in water. This conformational flexibility is severely limiting biological application of oligo-NSG. Here, we propose oligo-(N-substituted alanines) (oligo-NSA) as a new peptoid that forms a defined shape in water. A synthetic method established in this study enabled the first isolation and conformational study of optically pure oligo-NSA. Computational simulations, crystallographic studies and spectroscopic analysis demonstrated the well-defined extended shape of oligo-NSA realized by backbone steric effects. The new class of peptoid achieves the constrained conformation without any assistance of N-substituents and serves as an ideal scaffold for displaying functional groups in well-defined three-dimensional space, which leads to effective biomolecular recognition. </p> </div> </div> </div>

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