Jove
Visualize
Contact Us

Related Concept Videos

Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
Vector Algebra: Graphical Method01:10

Vector Algebra: Graphical Method

Vectors can be multiplied by scalars, added to other vectors, or subtracted from other vectors. The vector sum of two (or more) vectors is called the resultant vector or, for short, the resultant.
We use the laws of geometry to construct resultant vectors, followed by trigonometry to find vector magnitudes and directions. For a geometric construction of the sum of two vectors in a plane, we follow the parallelogram rule. Suppose two vectors are at arbitrary positions. Translate either one of...
Three-Dimensional Force System:Problem Solving01:30

Three-Dimensional Force System:Problem Solving

A three-dimensional force system refers to a scenario in which three forces act simultaneously in three different directions. This type of problem is commonly encountered in physics and engineering, where it is necessary to calculate the resultant force on the system, which can then be used to predict or analyze the behavior of the object or structure under consideration.
To solve a three-dimensional force system, first resolve each force into its respective scalar components. Do this using...
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
Here, in order to determine the magnitude of velocity and acceleration for point...
Topographic Surveying and Contours01:29

Topographic Surveying and Contours

Topographic surveying is critical for documenting the Earth's surface, focusing on capturing elevations, slopes, and natural and man-made features. It is essential in construction planning, water resource management, and land-use analysis. The primary outcome of such surveys is a topographic map, which uses contour lines to visually represent the shape and slope of the terrain, providing valuable insights into the landscape's characteristics.Contour lines are fundamental to understanding the...
Velocity and Position by Graphical Method01:34

Velocity and Position by Graphical Method

Velocity and position can be calculated from the known function of acceleration as a function of time. The total area under the acceleration-time graph and the velocity-time graph gives the change in velocity and position, respectively. In the case of an airplane, its acceleration is tracked using the inertial navigation system. The pilot provides the input of the airplane's initial position and velocity before takeoff. The inertial navigation system then uses the acceleration data to calculate...

You might also read

Related Articles

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

Sort by
Same author

Artificial intelligence as a tool for bionomic transects: the case of Isidella elongata (Esper, 1788) forests in the Western Mediterranean.

Marine environmental research·2026
Same author

CHIRLA: Comprehensive High-resolution Identification and Re-identification for Large-scale Analysis.

Scientific data·2026
Same author

Editorial: Methodology for emotion-aware education based on artificial intelligence.

Frontiers in artificial intelligence·2025
Same author

Photorealistic Learned Landscapes for Augmented Reality.

Journal of visualized experiments : JoVE·2025
Same author

Parallelized SLAM: Enhancing Mapping and Localization Through Concurrent Processing.

Sensors (Basel, Switzerland)·2025
Same author

Reliable Disparity Estimation Using Multiocular Vision with Adjustable Baseline.

Sensors (Basel, Switzerland)·2025
Same journal

Higher- and lower-level processing in strategic reading: Reconceptualising the Survey of Reading Strategies (SORS).

Cognitive processing·2026
Same journal

More caution or more lenient: deciphering the role of negative affect in recognition and inference.

Cognitive processing·2026
Same journal

Cognitive offloading, critical thinking and attitudes towards artificial intelligence in the era of ChatGPT: a comparative study of artificial intelligence-assisted and manual task performance in young adults.

Cognitive processing·2026
Same journal

Emojis vs. black-and-white and colored drawings: comparing living and non-living things in oral naming.

Cognitive processing·2026
Same journal

The impact of facial expressions on space- and object-based attention by gaze cues.

Cognitive processing·2026
Same journal

Feature interaction in metaphor aptness: the impact of topic-and-vehicle applicable features and semantic distances.

Cognitive processing·2026
See all related articles
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 Experiment Video

Updated: May 20, 2026

Three-Dimensional Mapping of the Rotation of Interactive Virtual Objects with Eye-Tracking Data
06:36

Three-Dimensional Mapping of the Rotation of Interactive Virtual Objects with Eye-Tracking Data

Published on: October 18, 2024

Topological visual mapping in robotics.

Anna Romero1, Miguel Cazorla

  • 1Department of Computer Science and Artificial Intelligence, University of Alicante, P.O. Box 99, 03080, Alicante, Spain. aromero@dccia.ua.es

Cognitive Processing
|July 19, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces a novel visual mapping method for robotics, utilizing topological information to build environment maps. The approach enhances simultaneous localization and mapping (SLAM) by grouping image features into graphs for robust navigation.

More Related Videos

Non-Invasive Modulation and Robotic Mapping of Motor Cortex in the Developing Brain
08:26

Non-Invasive Modulation and Robotic Mapping of Motor Cortex in the Developing Brain

Published on: July 1, 2019

Related Experiment Videos

Last Updated: May 20, 2026

Three-Dimensional Mapping of the Rotation of Interactive Virtual Objects with Eye-Tracking Data
06:36

Three-Dimensional Mapping of the Rotation of Interactive Virtual Objects with Eye-Tracking Data

Published on: October 18, 2024

Non-Invasive Modulation and Robotic Mapping of Motor Cortex in the Developing Brain
08:26

Non-Invasive Modulation and Robotic Mapping of Motor Cortex in the Developing Brain

Published on: July 1, 2019

Area of Science:

  • Robotics
  • Computer Vision
  • Artificial Intelligence

Background:

  • Mapping environments is crucial for robotic tasks like localization and obstacle avoidance.
  • Simultaneous Localization and Mapping (SLAM) is a significant challenge in robotics research.
  • Existing SLAM methods often rely on metric information, which can be sensitive to environmental changes.

Purpose of the Study:

  • To present a novel visual mapping method for robotics.
  • To utilize topological information instead of metric information for map construction.
  • To provide a complete SLAM solution, including image matching, topological map building, and loop-closing criteria.

Main Methods:

  • Image segmentation to group invariant features into distinct regions represented as graphs.
  • Graph Transformation Matching (GTM) algorithm for robust image feature matching and outlier removal.
  • Development of an algorithm for constructing topological maps based on image comparisons.

Main Results:

  • Demonstrated a complete visual SLAM method incorporating novel image matching and topological map construction.
  • Successfully applied graph transformation matching for robust feature matching and outlier rejection.
  • Introduced hysteresis behavior to improve graph construction stability.

Conclusions:

  • The proposed topological visual mapping method offers a complete and robust solution for SLAM.
  • The method effectively utilizes image segmentation and graph-based feature grouping for reliable mapping.
  • The approach shows promise for enhancing robotic navigation and environmental understanding.