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Related Concept Videos

Glassware Calibration01:11

Glassware Calibration

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Accurate calibration of glassware, such as volumetric flasks, pipettes, and burettes, is essential to ensure accurate measurements in the analytical laboratory. Calibration helps maintain consistency across measurements and prevents errors arising from inaccurate volumes.
Volumetric flasks: Volumetric flasks are designed to prepare aqueous solutions of precise volumes accurately with a calibration line on the neck. To calibrate a volumetric flask, it is important to fill it with distilled...
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Related Experiment Video

Updated: Nov 10, 2025

Optimized Sealing Process and Real-Time Monitoring of Glass-to-Metal Seal Structures
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LiDAR-Based Glass Detection for Improved Occupancy Grid Mapping.

Haileleol Tibebu1, Jamie Roche1, Varuna De Silva1

  • 1Institute of Digital Technologies, Loughborough University London, 3 Lesney Avenue, London E20 3BS, UK.

Sensors (Basel, Switzerland)
|April 3, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a novel method for detecting and localizing glass using LiDAR (light detection and ranging) sensors. The technique accurately maps environments with glass, improving robotic and automotive applications by overcoming LiDAR

Keywords:
LiDAR noise reductionglass detectionlocalisationoccupancy grid mapping

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Area of Science:

  • Robotics and Autonomous Systems
  • Sensor Technology
  • Computer Vision

Background:

  • Accurate environmental awareness is crucial for robotics and autonomous vehicles.
  • LiDAR (light detection and ranging) provides detailed environmental mapping but struggles with glass surfaces.
  • Glass in modern environments poses a significant challenge for LiDAR-based mapping.

Purpose of the Study:

  • To develop an effective method for detecting and localizing glass using LiDAR sensors.
  • To improve the accuracy of environmental mapping in the presence of glass.
  • To address the limitations of current LiDAR technology in detecting transparent or reflective surfaces.

Main Methods:

  • A novel two-step filtering approach is proposed for glass detection and localization.
  • The first filter analyzes variations in the standard deviation of neighboring point clouds.
  • The second filter refines results using changes in distance and intensity between neighboring pulses, estimating glass profile width.

Main Results:

  • The proposed method successfully detects and localizes glass surfaces.
  • Errors in occupancy grid maps caused by glass were eliminated.
  • The technique achieved a 96.2% accuracy in detecting frameless glass from long ranges, independent of intensity peaks.

Conclusions:

  • The developed method offers a robust solution for identifying glass using LiDAR.
  • This advancement significantly enhances the reliability of environmental mapping for autonomous systems.
  • The approach provides a high-accuracy, long-range glass detection capability crucial for real-world applications.