scholarly journals Boresight calibration of a terrestrial LiDAR scanning system

2021 ◽  
Author(s):  
Shahrzad Parandeh
Keyword(s):  
Mathematical Model ◽  
Laser Pulse ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Simulated Data ◽  
Laser Pulses ◽  
Three Dimensions ◽  
Measurement Unit ◽  
Scanning System ◽  
Terrestrial Lidar

Laser mapping has become quite popular in recent days due to its capability of providing information directly in three dimensions. A Terrestrial Laser Scanning (TLS) system operates by emitting and locating returned laser pulses. Locating the returned pulses requires knowing precisely for each laser pulse, the vehicle position (e.g. GPS), the attitude of the vehicle using Inertial Measurement Unit (lMU), the scanner angle when the laser pulse left the sensor, and the slant range to the surface for that pulse. One of the most critical sources of error in TLS or any other laser scanning system is the angular misalignment between the scanner and the IMU, which is called misalignment or boresight error. This error must be addressed before a TLS system can accurately produce data. The purpose of this research is to develop a method and identify the requirements for calculating the small misalignment angles between the laser scanner and the combined GPS/lMU solution for position and attitude. A mathematical model is developed in order to acquire the misalignment angles, using simulated data which consists of coordinates of target points, position of the scanner, rotation matrix of the IMU, and the product matrix (i. e. [LU., l1y, I1z]T) derived from the range and the MATLAB program which initially solves for the Projection Matrix using preset boresight angles (Rb). The equation is then rearranged to solve for the Rb as the goal is to obtain the same prearranged values that are initially used in the first part of the analysis. The calculation of the misalignment angles is considered to be successful as the prearranged Roll, Pitch, and Heading values are obtained after a few iteration, verifying that the mathematical model is sufficient for the purpose of calibrating the Terrestrial Laser Scanner.

scholarly journals Boresight calibration of a terrestrial LiDAR scanning system

2021 ◽  
Author(s):  
Shahrzad Parandeh
Keyword(s):  
Mathematical Model ◽  
Laser Pulse ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Simulated Data ◽  
Laser Pulses ◽  
Three Dimensions ◽  
Measurement Unit ◽  
Scanning System ◽  
Terrestrial Lidar

Laser mapping has become quite popular in recent days due to its capability of providing information directly in three dimensions. A Terrestrial Laser Scanning (TLS) system operates by emitting and locating returned laser pulses. Locating the returned pulses requires knowing precisely for each laser pulse, the vehicle position (e.g. GPS), the attitude of the vehicle using Inertial Measurement Unit (lMU), the scanner angle when the laser pulse left the sensor, and the slant range to the surface for that pulse. One of the most critical sources of error in TLS or any other laser scanning system is the angular misalignment between the scanner and the IMU, which is called misalignment or boresight error. This error must be addressed before a TLS system can accurately produce data. The purpose of this research is to develop a method and identify the requirements for calculating the small misalignment angles between the laser scanner and the combined GPS/lMU solution for position and attitude. A mathematical model is developed in order to acquire the misalignment angles, using simulated data which consists of coordinates of target points, position of the scanner, rotation matrix of the IMU, and the product matrix (i. e. [LU., l1y, I1z]T) derived from the range and the MATLAB program which initially solves for the Projection Matrix using preset boresight angles (Rb). The equation is then rearranged to solve for the Rb as the goal is to obtain the same prearranged values that are initially used in the first part of the analysis. The calculation of the misalignment angles is considered to be successful as the prearranged Roll, Pitch, and Heading values are obtained after a few iteration, verifying that the mathematical model is sufficient for the purpose of calibrating the Terrestrial Laser Scanner.

scholarly journals LOW COST MULTI-SENSOR ROBOT LASER SCANNING SYSTEM AND ITS ACCURACY INVESTIGATIONS FOR INDOOR MAPPING APPLICATION

2017 ◽  
Vol XLII-2/W8 ◽  
pp. 83-85 ◽  
Author(s):  
C. Chen ◽  
X. Zou ◽  
M. Tian ◽  
J. Li ◽  
W. Wu ◽  
...  
Keyword(s):  
Inertial Measurement Unit ◽  
Laser Scanning ◽  
Low Cost ◽  
Laser Scanner ◽  
Ground Truth ◽  
Measurement Unit ◽  
Scanning System ◽  
Ground Truth Data ◽  
Multiple Sensor ◽  
Laser Scanning System

In order to solve the automation of 3D indoor mapping task, a low cost multi-sensor robot laser scanning system is proposed in this paper. The multiple-sensor robot laser scanning system includes a panorama camera, a laser scanner, and an inertial measurement unit and etc., which are calibrated and synchronized together to achieve simultaneously collection of 3D indoor data. Experiments are undertaken in a typical indoor scene and the data generated by the proposed system are compared with ground truth data collected by a TLS scanner showing an accuracy of 99.2% below 0.25 meter, which explains the applicability and precision of the system in indoor mapping applications.

scholarly journals Post-mission misalignment angle calibration for airborne laser scanners

2021 ◽  
Author(s):  
Wendy Anne Dillane
Keyword(s):  
Laser Pulse ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Laser Pulses ◽  
Angular Misalignment ◽  
Data Set ◽  
Point Matching ◽  
Airborne Laser ◽  
Laser Scanners ◽  
Least Squares Adjustment

An Airborne Laser Scanning (ALS) system operates by locating returned laser pulses independently from all others. Locating the returned laser pulses requires knowing precisely for each laser pulse, the aircraft position (e.g. GPS), the attitude of the aircraft (e.g. IMU), the scanner angle when the laser pulse left the sensor, and the slant range to the terrain surface for that pulse. One of the most critical errors in ALS systems is the angular misalignment between the scanner and the IMU, which is called the misalignment or boresight error. This error must be addressed before an ALS system can accurately produce data. The purpose of this thesis was to develop and test a method of estimating the small misalignment angles between the laser scanner and the combined GPS/IMU solution for position and attitude. This method is semi-automated, requires no ground control and does not re-sample the ALS data in order to match the overlapping strips of data. A computer program called Misalignment Estimator was developed to estimate the misalignment angles using a least squares adjustment. The method was tested using a data set located at the Oshawa airport and provided by Optech. The misalignment angles were estimated to be -0.0178 degrees, -0.0829 degrees and 0.0320 degrees, for roll, pitch and heading respectively. The estimation of the misalignment angles was considered to be successful. Further research into automated point matching is recommended.

scholarly journals Post-mission misalignment angle calibration for airborne laser scanners

2021 ◽  
Author(s):  
Wendy Anne Dillane
Keyword(s):  
Laser Pulse ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Laser Pulses ◽  
Angular Misalignment ◽  
Data Set ◽  
Point Matching ◽  
Airborne Laser ◽  
Laser Scanners ◽  
Least Squares Adjustment

An Airborne Laser Scanning (ALS) system operates by locating returned laser pulses independently from all others. Locating the returned laser pulses requires knowing precisely for each laser pulse, the aircraft position (e.g. GPS), the attitude of the aircraft (e.g. IMU), the scanner angle when the laser pulse left the sensor, and the slant range to the terrain surface for that pulse. One of the most critical errors in ALS systems is the angular misalignment between the scanner and the IMU, which is called the misalignment or boresight error. This error must be addressed before an ALS system can accurately produce data. The purpose of this thesis was to develop and test a method of estimating the small misalignment angles between the laser scanner and the combined GPS/IMU solution for position and attitude. This method is semi-automated, requires no ground control and does not re-sample the ALS data in order to match the overlapping strips of data. A computer program called Misalignment Estimator was developed to estimate the misalignment angles using a least squares adjustment. The method was tested using a data set located at the Oshawa airport and provided by Optech. The misalignment angles were estimated to be -0.0178 degrees, -0.0829 degrees and 0.0320 degrees, for roll, pitch and heading respectively. The estimation of the misalignment angles was considered to be successful. Further research into automated point matching is recommended.

scholarly journals A LIGHTWEIGHT UAV-BASED LASER SCANNING SYSTEM FOR FOREST APPLICATION

2018 ◽  
Vol 24 (3) ◽  
pp. 318-334 ◽  
Author(s):  
Fernanda Magri Torres ◽  
Antonio Maria Garcia Tommaselli
Keyword(s):  
Laser Scanning ◽  
Accuracy Assessment ◽  
Low Cost ◽  
Temporal Frequency ◽  
Laser Scanner ◽  
Satellite System ◽  
Measurement Unit ◽  
Raspberry Pi ◽  
Scanning System ◽  
Point Density

Abstract Lightweight Unmanned Aerial Vehicles (UAVs) have become a cost effective alternative for studies which use aerial Remote Sensing with high temporal frequency requirements for small areas. Laser scanner devices are widely used for rapid tridimensional data acquisition, mainly as a complementary data source to photogrammetric surveying. Recent studies using laser scanner systems onboard UAVs for forestry inventory and mapping applications have presented encouraging results. This work describes the development and accuracy assessment of a low cost mapping platform composed by an Ibeo Lux scanner, a GNSS (Global Navigation Satellite System) antenna, an Inertial Navigation System Novatel Span-IGM-S1, integrating a GNSS receiver and an IMU (Inertial Measurement Unit), a Raspberry PI portable computer and an octopter UAV. The system was assessed in aerial mode using an UAV octopter developed by SensorMap Company. The resulting point density in a plot with trees concentration was also evaluated. The point density of this device is lower than conventional Airborne Laser Systems but the results showed that altimetric accuracy with this system is around 30 cm, which is acceptable for forest applications. The main advantages of this system are their low weight and low cost, which make it attractive for several applications.

scholarly journals LOW-COST WHEELED ROBOT-BORNE LASER SCANNING SYSTEM FOR INDOOR AND OUTDOOR 3D MAPPING APPLICATION

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 1155-1159
Author(s):  
W. Wu ◽  
C. Chen ◽  
Y. Cong ◽  
Z. Dong ◽  
J. Li ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Low Cost ◽  
Laser Scanner ◽  
Point Clouds ◽  
Measurement Unit ◽  
Scanning System ◽  
Outdoor Scenes ◽  
Wheeled Robot ◽  
Laser Scanning System ◽  
Indoor And Outdoor

<p><strong>Abstract.</strong> Aiming to accomplish automatic and real-time three-dimensional mapping in both indoor and outdoor scenes, a low-cost wheeled robot-borne laser scanning system is proposed in this paper. The system includes a laser scanner, an inertial measurement unit, a modified turtlebot3 two-wheel differential chassis and etc. To achieve a globally consistent map, the system performs global trajectory optimization after detecting the loop closure. Experiments are undertaken in two typical indoor/outdoor scenes that is an underground car park and a road environment in the campus of Wuhan University. The point clouds acquired by the proposed system are quantitatively evaluated by comparing the derived point clouds with the ground truth data collected by a RIEGL VZ 400 laser scanner. The results present an accuracy of 90% points below 0.1 meter error in the tested scene, showing that its applicability and potential in indoor and mapping applications.</p>

Design of Light-Small Mobile 3D Laser Measurement System

2013 ◽  
Vol 405-408 ◽  
pp. 3032-3036
Author(s):  
Yi Bo Sun ◽  
Xin Qi Zheng ◽  
Zong Ren Jia ◽  
Gang Ai
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Digital Camera ◽  
Scanning System ◽  
Point Cloud Data ◽  
3D Laser Scanning ◽  
Large Area ◽  
Cloud Data ◽  
Laser Scanning System

At present, most of the commercial 3D laser scanning measurement systems do work for a large area and a big scene, but few shows their advantage in the small area or small scene. In order to solve this shortage, we design a light-small mobile 3D laser scanning system, which integrates GPS, INS, laser scanner and digital camera and other sensors, to generate the Point Cloud data of the target through data filtering and fusion. This system can be mounted on airborne or terrestrial small mobile platform and enables to achieve the goal of getting Point Cloud data rapidly and reconstructing the real 3D model. Compared to the existing mobile 3D laser scanning system, the system we designed has high precision but lower cost, smaller hardware and more flexible.

Design and Implementation of Machine Vision Automatic Laser Scanning System

2011 ◽  
Vol 201-203 ◽  
pp. 940-943
Author(s):  
Heng Feng Yan ◽  
Jun Shao ◽  
Ji Min Chen
Keyword(s):  
Machine Vision ◽  
Reference Point ◽  
Laser Scanning ◽  
Laser Scanner ◽  
Scanning System ◽  
Design And Implementation ◽  
Coordination Systems ◽  
Specific Position ◽  
Laser Scanning System

This paper introduces a solution for laser scanning system, which utilizes machine vision technology. It includes algorithm for positioning and matrix for scanning control. The system can be used to detect an object and laser mark on specific position. This work explains how to use one CCD to catch an object’s position variation relative to a reference point, and how to translate the different coordination systems for laser scanner etc.

Calibration of a multiple axes 3-D laser scanning system consisting of robot, portable laser scanner and turntable

Optik ◽  
2011 ◽  
Vol 122 (4) ◽  
pp. 324-329 ◽  
Author(s):  
Jianfeng Li ◽  
Ming Chen ◽  
Xuebi Jin ◽  
Yu Chen ◽  
Zhiyong Dai ◽  
...  
Keyword(s):  
Laser Scanning ◽  
Laser Scanner ◽  
Scanning System ◽  
Laser Scanning System
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