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Related Concept Videos

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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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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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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Fusion of the SLAM with Wi-Fi-Based Positioning Methods for Mobile Robot-Based Learning Data Collection,

Gunwoo Lee1, Byeong-Cheol Moon1, Sangjae Lee1

  • 1Department of Computer Science, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea.

Sensors (Basel, Switzerland)
|September 16, 2020
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Summary

This study introduces a novel robot localization method using a signal fluctuation matrix and an enhanced Viterbi algorithm. The approach significantly improves tracking accuracy for mobile robots in various environments.

Keywords:
indoor localizationlearning data collectionmobile robot

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Signal Processing

Background:

  • Accurate mobile robot localization is crucial for robotic services but challenging with dead reckoning alone.
  • Existing methods struggle with speed and precision in determining robot positions within a workspace.
  • Integrating map data with sensor information is complex for real-time applications.

Purpose of the Study:

  • To develop an advanced algorithm for precise mobile robot location tracking.
  • To enhance the accuracy and efficiency of robot localization in dynamic environments.
  • To propose a data fusion technique for improved learning data collection.

Main Methods:

  • A novel signal fluctuation matrix was developed for enhanced localization.
  • An extended Viterbi algorithm was combined with odometer data for tracking.
  • Simultaneous localization and mapping (SLAM) and Wi-Fi fingerprinting were fused for data collection.

Main Results:

  • The proposed methods demonstrated accurate and efficient robot location tracking in experimental tests.
  • The fusion technique successfully collected high-quality learning data for robot localization.
  • The algorithm significantly improved upon traditional dead reckoning methods.

Conclusions:

  • The developed signal fluctuation matrix and tracking algorithm enhance mobile robot localization accuracy.
  • The fusion of SLAM and Wi-Fi fingerprinting provides a robust method for data acquisition.
  • The proposed techniques show potential for application in the Internet of Things and other fields.