Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Types of Global Positioning System Surveys01:30

Types of Global Positioning System Surveys

49
GPS surveying methods vary in application, accuracy, and data collection techniques, catering to diverse surveying and mapping needs. Static GPS, kinematic GPS, and real-time kinematic (RTK) surveying are widely used. Each technique offers distinct advantages.Static GPS involves placing one receiver at a known reference point and another at the target point. It collects exact positional data by observing multiple satellite ranges over an extended period, achieving centimeter-level accuracy for...
49
Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device01:30

Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device

21
Surveyors use Global Positioning System (GPS) technology to measure the precise location and elevation of points on Earth. In a recent survey, GPS receivers were used to determine the coordinates and elevations of two park monuments. The process involved careful mission planning, data collection, and correction to ensure accuracy. The survey began with mission planning to identify optimal satellite visibility and minimize Position Dilution of Precision (PDOP). A geodetic control point...
21

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Camera-LiDAR Wide Range Calibration in Traffic Surveillance Systems.

Sensors (Basel, Switzerland)·2025
Same author

SVS-VPR: A Semantic Visual and Spatial Information-Based Hierarchical Visual Place Recognition for Autonomous Navigation in Challenging Environmental Conditions.

Sensors (Basel, Switzerland)·2024
Same author

Placement Method of Multiple Lidars for Roadside Infrastructure in Urban Environments.

Sensors (Basel, Switzerland)·2023
Same author

Hair Growth Effect of DN106212 in C57BL/6 Mouse and Its Network Pharmacological Mechanism of Action.

Current issues in molecular biology·2023
Same author

Characterization of Channeling Effects Applied to Extended-Release Matrix Tablets Containing Pirfenidone.

Chemical & pharmaceutical bulletin·2023
Same author

Camera-LiDAR Fusion Method with Feature Switch Layer for Object Detection Networks.

Sensors (Basel, Switzerland)·2022

Related Experiment Video

Updated: Jun 3, 2025

Three-dimensional Super Resolution Microscopy of F-actin Filaments by Interferometric PhotoActivated Localization Microscopy iPALM
11:57

Three-dimensional Super Resolution Microscopy of F-actin Filaments by Interferometric PhotoActivated Localization Microscopy iPALM

Published on: December 1, 2016

10.7K

Initial Pose Estimation Method for Robust LiDAR-Inertial Calibration and Mapping.

Eun-Seok Park1, Saba Arshad2, Tae-Hyoung Park1

  • 1Department of Intelligent Systems & Robotics, Chungbuk National University, Cheongju 28644, Republic of Korea.

Sensors (Basel, Switzerland)
|January 8, 2025
PubMed
Summary

This study introduces a new method for calibrating handheld LiDAR-IMU systems, improving 3D mapping accuracy. The approach enhances data quality for mobile scanning applications.

Keywords:
3D LiDARLiDAR-IMU calibrationhandheld devicepose estimation

More Related Videos

Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb
08:24

Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb

Published on: August 30, 2016

10.2K
Determining 3D Flow Fields via Multi-camera Light Field Imaging
14:25

Determining 3D Flow Fields via Multi-camera Light Field Imaging

Published on: March 6, 2013

16.6K

Related Experiment Videos

Last Updated: Jun 3, 2025

Three-dimensional Super Resolution Microscopy of F-actin Filaments by Interferometric PhotoActivated Localization Microscopy iPALM
11:57

Three-dimensional Super Resolution Microscopy of F-actin Filaments by Interferometric PhotoActivated Localization Microscopy iPALM

Published on: December 1, 2016

10.7K
Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb
08:24

Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb

Published on: August 30, 2016

10.2K
Determining 3D Flow Fields via Multi-camera Light Field Imaging
14:25

Determining 3D Flow Fields via Multi-camera Light Field Imaging

Published on: March 6, 2013

16.6K

Area of Science:

  • Robotics and Sensor Fusion
  • Geomatics Engineering
  • Computer Vision

Background:

  • Handheld LiDAR scanners offer flexible 3D data capture but face calibration challenges due to sensor mobility.
  • Accurate calibration of LiDAR-IMU systems is critical for precise mapping in Simultaneous Localization and Mapping (SLAM).
  • Existing calibration methods struggle with noise and efficiency, especially for mobile indoor environments.

Purpose of the Study:

  • To develop a robust initial pose calibration method for handheld LiDAR-IMU systems in indoor environments.
  • To enhance the accuracy and efficiency of LiDAR-IMU calibration for mobile 3D mapping applications.

Main Methods:

  • A novel plane detection algorithm is proposed to filter noise from mobile LiDAR scans.
  • A planes-aided calibration method is introduced to estimate the initial pose of LiDAR-IMU systems.
  • The method focuses on precise alignment of extrinsic sensor parameters.

Main Results:

  • The proposed plane detection effectively removes scanning noise, yielding accurate planes for pose estimation.
  • The planes-aided calibration method achieves robust and efficient LiDAR-IMU initial pose estimation.
  • Experimental results show reduced calibration errors and improved computational efficiency compared to existing techniques.

Conclusions:

  • The developed method provides a robust solution for initial pose calibration of handheld LiDAR-IMU systems.
  • This advancement contributes to more accurate and efficient 3D mapping in architecture, civil engineering, and robotics.
  • The approach is particularly beneficial for indoor mapping applications where sensor mobility is a key factor.