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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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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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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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Related Experiment Video

Updated: Aug 23, 2025

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
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Development of an Online Adaptive Parameter Tuning vSLAM Algorithm for UAVs in GPS-Denied Environments.

Chieh-Li Chen1, Rong He1, Chao-Chung Peng1

  • 1Department of Aeronautics and Astronautics, National Cheng Kung University, Tainan 701, Taiwan.

Sensors (Basel, Switzerland)
|October 27, 2022
PubMed
Summary

This study introduces an adaptive visual simultaneous localization and mapping (vSLAM) system for unmanned aerial vehicles (UAVs). The enhanced system improves positioning accuracy and robustness by dynamically adjusting parameters, overcoming limitations of traditional Global Navigation Satellite Systems (GNSS).

Keywords:
GPS-denied environmentsS-PTAMadaptive tuninginertial measurement unit (IMU)mahony complementary filterstereo visionvSLAM

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Area of Science:

  • Robotics
  • Computer Vision
  • Navigation Systems

Background:

  • Unmanned Aerial Vehicles (UAVs) heavily rely on Global Navigation Satellite Systems (GNSS) for positioning.
  • GNSS is susceptible to environmental interference and ineffective indoors, limiting UAV applications.
  • Existing visual simultaneous localization and mapping (vSLAM) systems face challenges with parameter tuning, impacting accuracy.

Purpose of the Study:

  • To develop an enhanced vSLAM system for UAVs that overcomes GNSS limitations.
  • To improve the accuracy and robustness of UAV localization in unknown environments.
  • To address the challenge of manual threshold setting in feature matching for vSLAM.

Main Methods:

  • Implemented a stereo-based vSLAM algorithm fused with onboard Inertial Measurement Unit (IMU) data.
  • Developed an online adaptive matching threshold based on keyframe poses to replace manual Hamming distance thresholds.
  • Integrated an adaptive gain tuning for the Mahony complementary filter and a static state detection algorithm for IMU-vSLAM integration.

Main Results:

  • The developed online adaptive matching threshold significantly improved vSLAM positioning accuracy.
  • Dynamic tuning of the IMU's Mahony complementary filter enhanced attitude estimation during aggressive motions.
  • The static state detection algorithm improved the initial guess for the bundle adjustment algorithm, boosting overall performance.

Conclusions:

  • The proposed online adaptive parameter tuning algorithm effectively enhances vSLAM accuracy and robustness for UAVs.
  • The integrated system provides reliable localization information without reliance on GNSS signals.
  • This research expands the potential applications of UAVs in GNSS-denied or indoor environments.