Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Influence of Earth's Curvature and Atmospheric Refraction on Leveling01:26

Influence of Earth's Curvature and Atmospheric Refraction on Leveling

During leveling, the Earth's curvature and atmospheric refraction introduce deviations in the line of sight from a true horizontal reference. When the line of sight is leveled, it remains perpendicular to the plumb line only at a single point. Beyond this, it deviates due to the Earth’s curvature, represented by the correction C. For a sight distance D, the deviation can be derived using the relationship:This relationship shows that the deviation increases quadratically with distance. Over a...
Curvilinear Motion: Normal and Tangential Components01:27

Curvilinear Motion: Normal and Tangential Components

When a car traverses a curved road, its motion can be elucidated by breaking it down into tangential and normal components. The car-centric coordinates attached to the vehicle move with it.
The positive direction of the t-axis aligns with the increasing position of the car along the curved path, denoted by the unit vector ut. Simultaneously, the n-axis, perpendicular to the t-axis, dissects the curved path into differential arc segments, each forming the arc of a circle with a radius of...
Sight Distance in a Vertical Curve01:29

Sight Distance in a Vertical Curve

Sight distance on vertical curves is critical in roadway design. It ensures drivers can see far enough ahead to identify and respond to hazards effectively. This directly impacts safety, driver comfort, and the overall efficiency of the transportation network.Vertical curves are classified into crest and sag curves based on their geometry. For crest curves, sight distance is determined by the line of sight between a driver's eye and a small object on the road's surface. Design parameters for...
Curvilinear Motion: Rectangular Components01:23

Curvilinear Motion: Rectangular Components

Curvilinear motion characterizes the movement of a particle or object along a curved path, notably evident when envisioning a car navigating a winding road. If the car starts at point A, its position vector is established within a fixed frame of reference, where the ratio of the position vector to its magnitude signifies the unit vector pointing in the position vector's direction.
As the car advances, its position evolves over time. Quantifying the car's velocity involves computing the time...
Degree of Curvature and Radius of Curvature01:19

Degree of Curvature and Radius of Curvature

The degree of curvature and the radius of curvature are fundamental concepts in determining the sharpness or smoothness of a curve. The degree of curvature is a measure of how steeply a curve bends and can be determined using the chord basis or the arc basis. In the chord basis method, the degree of curvature is defined as the central angle subtended by a chord of 30.48 meters, helping in the calculation of the radius of the curve. The arc basis method defines the degree of curvature as the...
Introduction to Vertical Curves01:24

Introduction to Vertical Curves

Vertical curves are parabolic transitions that connect different grades on highways and railroads, ensuring a smooth alignment between back and forward tangents. The back tangent represents the initial grade, while the forward tangent defines the subsequent grade. These curves can be symmetrical, with equal tangent lengths, or nonsymmetrical, with varying lengths. The key points defining a vertical curve include the Point of Vertical Intersection (P.V.I.), where the tangents meet; the Point of...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Personalized causal explanations of a robot's behavior.

Frontiers in robotics and AI·2025
Same author

Enhancing Robotic Perception through Synchronized Simulation and Physical Common-Sense Reasoning.

Sensors (Basel, Switzerland)·2024
Same author

Editorial: Socially, culturally and contextually aware robots.

Frontiers in robotics and AI·2023
Same author

Multi-Site Cross-Site Inter-Rater and Test-Retest Reliability and Construct Validity of the MarkVCID White Matter Hyperintensity Growth and Regression Protocol.

Journal of Alzheimer's disease : JAD·2023
Same author

Microwave-Assisted Synthesis of Zeolite A from Metakaolinite for CO<sub>2</sub> Adsorption.

International journal of molecular sciences·2023
Same author

Real-Time Embedded Eye Image Defocus Estimation for Iris Biometrics.

Sensors (Basel, Switzerland)·2023

Related Experiment Video

Updated: May 23, 2026

Dynamic Navigation for Dental Implant Placement
05:42

Dynamic Navigation for Dental Implant Placement

Published on: September 13, 2022

Curvature-based environment description for robot navigation using laser range sensors.

Ricardo Vázquez-Martín1, Pedro Núñez, Antonio Bandera

  • 1Departamento de Tecnología Electrónica, University of Málaga, E.T.S.I. Telecomunicación, Campus Teatinos, Málaga, Spain; E-Mails: rvmartin@uma.es ; ajbandera@uma.es ; fsandoval@uma.es.

Sensors (Basel, Switzerland)
|March 31, 2012
PubMed
Summary

This study introduces a novel method for mobile robot navigation using 2D laser range sensors. It enhances feature detection and environment description for improved robot perception and localization.

Keywords:
adaptive curvature estimationlaser scan data segmentationmobile robot navigation

More Related Videos

Automatic Laser-based Geometry Capture for Finite Element Analysis of Weld Beads
07:58

Automatic Laser-based Geometry Capture for Finite Element Analysis of Weld Beads

Published on: July 25, 2025

Related Experiment Videos

Last Updated: May 23, 2026

Dynamic Navigation for Dental Implant Placement
05:42

Dynamic Navigation for Dental Implant Placement

Published on: September 13, 2022

Automatic Laser-based Geometry Capture for Finite Element Analysis of Weld Beads
07:58

Automatic Laser-based Geometry Capture for Finite Element Analysis of Weld Beads

Published on: July 25, 2025

Area of Science:

  • Robotics
  • Computer Vision
  • Sensor Data Processing

Background:

  • Mobile robot navigation relies on accurate environment perception.
  • Existing feature detection methods can be sensitive to noise and viewpoint changes.
  • 2D laser range sensors provide crucial data for robot localization.

Purpose of the Study:

  • To propose a robust feature detection and description approach for mobile robot navigation.
  • To improve environment characterization using 2D laser scan data.
  • To develop a segmentation method resilient to noise and viewpoint variations.

Main Methods:

  • A two-module process: sensor data segmentation and feature detection/characterization.
  • Segmentation involves clustering range readings and estimating curvature using a novel triangle-area representation.
  • The triangle-area representation adapts to local scan variations, enhancing noise robustness.

Main Results:

  • The proposed method effectively segments laser scans into meaningful geometric primitives (lines, curves).
  • Environment features like corners and edges are accurately identified and described.
  • The approach demonstrates robustness against noise and viewpoint changes in real-world data.

Conclusions:

  • The developed feature detection and description method enhances mobile robot navigation capabilities.
  • The novel segmentation technique provides a robust foundation for environment characterization.
  • This approach offers improved performance in diverse and noisy environments.