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Related Concept Videos

Introduction to Global Positioning System01:30

Introduction to Global Positioning System

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The Global Positioning System (GPS) revolutionized positioning on Earth, providing precise location data through satellite ranging. The GPS system was developed in 1978 by the U.S. Department of Defense  for military use, and it became available for civilian applications in 1983, transforming fields including navigation, fleet management, and time synchronization for telecommunications systems.GPS consists of satellites in medium Earth orbit, about 20,200 kilometers above the surface,...
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Types of Global Positioning System Surveys01:30

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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...
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Field Application of Global Positioning System01:28

Field Application of Global Positioning System

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The Global Positioning System (GPS) has become an indispensable tool in fieldwork, offering unparalleled precision and efficiency for surveying, navigation, and infrastructure development. By harnessing signals from a constellation of satellites, GPS receivers determine the location of objects with remarkable speed and accuracy, often completing calculations within a second.Advantages of Modern GPS TechnologyContemporary GPS receivers are designed to meet the practical demands of field...
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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

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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...
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Errors in Global Positioning System01:26

Errors in Global Positioning System

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Global Positioning System (GPS) technology has revolutionized navigation and positioning, but its accuracy is often compromised by various errors. These errors, stemming from environmental, satellite, and receiver-related factors, require careful mitigation to ensure reliable performance across applications.Atmospheric ErrorsGPS signals travel through the Earth’s ionosphere and troposphere, introducing delays which affect accuracy. The ionosphere is strongly influenced by charged particles,...
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¹H NMR Signal Integration: Overview00:58

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The intensity of a signal, which can be represented by the area under the peak, depends on the number of protons contributing to that signal. The area under each peak is shown as a vertical line called an integral, with the integral value listed under it, as seen in the proton NMR spectrum of benzyl acetate. Each integral value is divided by the smallest integral value to obtain the ratio of the number of protons producing each signal. The ratio reveals the relative number of protons and not...
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GNSS/IMU/ODO/LiDAR-SLAM Integrated Navigation System Using IMU/ODO Pre-Integration.

Le Chang1, Xiaoji Niu1, Tianyi Liu1

  • 1GNSS Research Center, Wuhan University, 129 Luoyu Road, Wuhan 430079, China.

Sensors (Basel, Switzerland)
|August 23, 2020
PubMed
Summary

This study introduces a multi-sensor navigation system combining GNSS, IMU, ODO, and LiDAR-SLAM for enhanced accuracy. The integrated system significantly reduces navigation drift and improves robustness, especially in challenging environments with poor GNSS signals.

Keywords:
GNSSIMULiDAR-SLAMODOgraph optimizationpre-integration

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Area of Science:

  • Robotics and Autonomous Systems
  • Geomatics Engineering
  • Navigation and Positioning

Background:

  • Accurate and robust navigation is critical for autonomous systems, especially in environments with degraded Global Navigation Satellite System (GNSS) signals.
  • Existing integrated navigation systems often struggle with sensor drift and environmental limitations, impacting performance in challenging scenarios like tunnels.

Purpose of the Study:

  • To propose and evaluate a novel multi-sensor integrated navigation system fusing GNSS, Inertial Measurement Unit (IMU), Odometer (ODO), and LiDAR-SLAM.
  • To enhance navigation accuracy and robustness by mitigating sensor drift and improving performance in GNSS-denied or feature-poor environments.

Main Methods:

  • Developed a front-end dead reckoning system using IMU/ODO, incorporating odometer data to reduce IMU drift.
  • Implemented a back-end graph optimization fusing GNSS, IMU/ODO pre-integration, and LiDAR-SLAM relative pose, utilizing a sliding window approach.
  • Conducted land vehicle tests in open-sky and tunnel scenarios to validate system performance.

Main Results:

  • The proposed system demonstrated significant reductions in navigation drift during simulated GNSS outages compared to conventional GNSS/INS/ODO integration (e.g., 62.8% North, 72.3% East, 52.1% Height position error reduction).
  • Yaw error was reduced by 62.1%.
  • In GNSS/IMU/LiDAR-SLAM integration, odometer assistance reduced vertical error by 72.3%. The system maintained short-term SLAM in tunnels and reduced forward positioning drift.

Conclusions:

  • The multi-sensor fusion of GNSS, IMU, ODO, and LiDAR-SLAM effectively improves navigation accuracy and robustness.
  • The integration of odometer data is crucial for mitigating drift, particularly in environments with limited GNSS availability and insufficient features for LiDAR-SLAM.
  • The proposed system offers a reliable solution for autonomous navigation in challenging conditions where GNSS signals are weak and environmental features are sparse.