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Related Concept Videos

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Distance Corrections

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To achieve precise distance measurements, especially in surveying and construction, certain corrections must be applied to account for potential sources of error like the standardization errors, temperature variations, and slope adjustments.Standardization error emerges when measurement equipment undergoes changes, such as wear, repairs, or weather impacts. To address this, surveyors compare the equipment’s readings to a standard. This process identifies any deviation that might lead to...
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Common Leveling Mistakes and Errors01:17

Common Leveling Mistakes and Errors

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A survey team is tasked with determining the elevation difference between points Point A and Point B, separated by uneven terrain. They use a leveling instrument and a leveling rod.Common MistakesMisreading the Rod: During a backsight reading at Point A, the instrumentman observes the rod partially obscured by tall grass. Instead of reading 1.135 m, they mistakenly record 1.735 m due to the misalignment of the crosshair with the wrong graduation. This error adds 0.600 m to all subsequent...
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Differential leveling is a precise method in surveying used to determine the elevation difference between two points. Its primary goal is to establish accurate vertical measurements to create level surfaces or grade lines critical for designing and constructing infrastructures such as roads, bridges, and buildings.The procedure for differential leveling begins with setting up and leveling the instrument at a point where the benchmark can be seen. The level rod is held on the benchmark (BM), and...
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Distance Measurements by Taping01:18

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Tapes are essential in surveying for accurate, durable, and short-distance measurements. Made from lightweight, nylon-coated steel, they offer flexibility and strength for rugged outdoor use. The nylon coating protects against rust and wear, extending the tape's life. Standard lengths, around 30 meters, are marked in meters and millimeters for precision.Surveyors select tapes based on site conditions and accuracy needs. Lightweight, nylon-coated tapes are commonly used for ease of handling and...
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Types of Global Positioning System Surveys01:30

Types of Global Positioning System Surveys

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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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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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UnVELO: Unsupervised Vision-Enhanced LiDAR Odometry with Online Correction.

Bin Li1, Haifeng Ye1, Sihan Fu1

  • 1Faculty of the College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China.

Sensors (Basel, Switzerland)
|April 28, 2023
PubMed
Summary

This study introduces UnVELO, an unsupervised visual-LiDAR odometry method that enhances LiDAR data with visual information for more robust robot navigation. UnVELO improves accuracy and efficiency in challenging conditions.

Keywords:
deep learningmulti-sensor fusiontest time optimizationvisual–LiDAR odometry

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Area of Science:

  • Robotics
  • Computer Vision
  • Sensor Fusion

Background:

  • Visual and LiDAR data offer complementary information for vision tasks.
  • Existing visual-LiDAR odometries (VLOs) are under-explored, with most focusing on single modalities.

Purpose of the Study:

  • To propose a novel unsupervised visual-LiDAR odometry (VLO) method.
  • To develop a LiDAR-dominant fusion scheme for enhanced VLO performance.

Main Methods:

  • Implemented an unsupervised vision-enhanced LiDAR odometry (UnVELO) using a LiDAR-dominant approach.
  • Fused 3D LiDAR points (spherical projection) with visual information to create dense vertex and color maps.
  • Utilized point-to-plane geometric loss and photometric visual loss, incorporating an online pose-correction module.

Main Results:

  • UnVELO demonstrated superior performance compared to previous two-frame learning methods on KITTI and DSEC datasets.
  • The LiDAR-dominant fusion approach improved robustness to illumination variations and online pose correction efficiency.
  • Achieved competitive results against hybrid methods integrating global optimization.

Conclusions:

  • The proposed UnVELO method offers an effective approach to unsupervised visual-LiDAR odometry.
  • LiDAR-dominant fusion with dense representations enhances visual-LiDAR integration and robustness.
  • UnVELO presents a promising direction for advancing autonomous navigation systems.