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Related Concept Videos

Plotting and Calibrating the Root Locus01:19

Plotting and Calibrating the Root Locus

Root loci often diverge as system poles shift from the real axis to the complex plane. Key points in this transition are the breakaway and break-in points, indicating where the root locus leaves and reenters the real axis. The branches of the root locus form an angle of 180/n degrees with the real axis, where n is the number of branches at a breakaway or break-in point.
The maximum gain occurs at the breakaway points between open-loop poles on the real axis, while the minimum gain is observed...
Field Application of Global Positioning System01:28

Field Application of Global Positioning System

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...
Types of Global Positioning System Surveys01:30

Types of Global Positioning System Surveys

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...
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

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Related Experiment Videos

An O(N(2)) square root unscented Kalman Filter for visual simultaneous localization and mapping.

Steven A Holmes1, Georg Klein, David W Murray

  • 1Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, UK. sah@robots.ox.ac.uk

IEEE Transactions on Pattern Analysis and Machine Intelligence
|May 16, 2009
PubMed
Summary

This study introduces the Square Root Unscented Kalman Filter (SRUKF) for efficient visual simultaneous localization and mapping (SLAM). The SRUKF achieves video-rate performance with improved consistency over the Extended Kalman Filter (EKF).

Related Experiment Videos

Area of Science:

  • Robotics
  • Computer Vision
  • Estimation Theory

Background:

  • Simultaneous Localization and Mapping (SLAM) is crucial for autonomous systems.
  • Conventional Unscented Kalman Filter (UKF) offers improved nonlinearity handling over Extended Kalman Filter (EKF) but suffers from high computational complexity.
  • Existing SLAM algorithms struggle with video-rate processing for complex scenes.

Purpose of the Study:

  • To develop a computationally efficient Square Root Unscented Kalman Filter (SRUKF) for video-rate visual SLAM.
  • To demonstrate the SRUKF's capability for real-time single-camera SLAM applications.
  • To compare the performance and complexity of SRUKF against EKF and UKF.

Main Methods:

  • Implementation of the Square Root Unscented Kalman Filter (SRUKF) algorithm.
  • Application of SRUKF to visual SLAM using single-camera input.
  • Comparative analysis of SRUKF, UKF, and EKF using synthesized and live video-rate data.

Main Results:

  • SRUKF achieves equivalent accuracy to UKF with reduced complexity (O(N^2)).
  • SRUKF enables video-rate visual SLAM, outperforming EKF in consistency.
  • SRUKF demonstrates superior consistency over EKF in synthesized data trials, though with higher computational cost for large scenes.

Conclusions:

  • SRUKF is a viable and efficient algorithm for real-time visual SLAM.
  • The SRUKF offers a practical solution for achieving video-rate performance in visual SLAM systems.
  • SRUKF presents a trade-off between enhanced consistency and computational cost compared to EKF.