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

Inertial Frames of Reference01:03

Inertial Frames of Reference

7.0K
Newton’s first law is usually considered to be a statement about reference frames. It provides a method for identifying a special type of reference frame: the inertial reference frame. In principle, we can make the net force on a body zero. If its velocity relative to a given frame is constant, then that frame is said to be inertial. So, by definition, an inertial reference frame is a reference frame where Newton's first law holds valid. Newton's first law applies to objects with...
7.0K
Absolute Motion Analysis- General Plane Motion01:24

Absolute Motion Analysis- General Plane Motion

210
Visualize a drone, with its propellers spinning rapidly, hovering mid-air. The fascinating movements and operations of this drone can be comprehended by applying the principle of general plane motion.
As the drone's propellers rotate, an upward force is generated that counteracts the force of gravity, enabling the drone to lift off from the ground. This initial movement of the drone is along a straight path, representing a form of translational motion. In this phase, every point on the...
210
Gyroscope01:02

Gyroscope

2.9K
A gyroscope is defined as a spinning disk in which the axis of rotation is free to assume any orientation. When spinning, the orientation of the spin axis is unaffected by the orientation of the body that encloses it. The body or vehicle enclosing the gyroscope can be moved from place to place, while the orientation of the spin axis remains the same. This makes gyroscopes very useful in navigation, especially where magnetic compasses cannot be used, such as in crewed and crewless spacecraft,...
2.9K
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

386
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...
386
Gyroscope: Precession01:24

Gyroscope: Precession

4.0K
Precession can be demonstrated effectively through a spinning top. If a spinning top is placed on a flat surface near the surface of the Earth at a vertical angle and is not spinning, it will fall over due to the force of gravity producing a torque acting on its center of mass. However, if the top is spinning on its axis, it precesses about the vertical direction, rather than topple over due to this torque. Precessional motion is a combination of a steady circular motion of the axis and the...
4.0K
Relative Motion Analysis using Rotating Axes01:25

Relative Motion Analysis using Rotating Axes

447
Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame.
However, to express the relative position of point B relative to point A, an additional frame of reference, denoted as x'y', is necessary. This additional frame not only translates but also rotates relative to the fixed frame, making it...
447

You might also read

Related Articles

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

Sort by
Same author

Assessment of anthropogenic macro-litter and its impacts on the seagrass meadows of the remote Andaman and Nicobar Islands, northern Indian Ocean.

Marine pollution bulletin·2026
Same author

Prospective Validation of the MIRACLE<sub>2</sub> Score for Early Neurological Stratification After Out-of-Hospital Cardiac-Arrest: The GLOBAL-MIRACLE Registry.

Circulation. Cardiovascular interventions·2026
Same author

Comparative Efficacy and Safety of Hybrid Endoscopic Submucosal Dissection for Colorectal Neoplasia: A Systematic Review and Meta-Analysis.

JGH open : an open access journal of gastroenterology and hepatology·2026
Same author

Thrombotic Microangiopathy Secondary to Capnocytophaga Sepsis: A Case Report.

Cureus·2026
Same author

MA-EVIO: A Motion-Aware Approach to Event-Based Visual-Inertial Odometry.

Sensors (Basel, Switzerland)·2025
Same author

The Coronary Microcirculation Re-explored: Pathophysiological Insights and Clinical Implications.

European cardiology·2025

Related Experiment Video

Updated: Jun 3, 2025

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field
06:52

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field

Published on: May 26, 2020

7.9K

Event-Based Visual/Inertial Odometry for UAV Indoor Navigation.

Ahmed Elamin1,2, Ahmed El-Rabbany1, Sunil Jacob3

  • 1Civil Engineering Department, Faculty of Engineering and Architectural Science, Toronto Metropolitan University, Toronto, ON M5B 2K3, Canada.

Sensors (Basel, Switzerland)
|January 11, 2025
PubMed
Summary

This study introduces an event-based visual-inertial odometry system for precise indoor navigation. The approach significantly reduces errors and achieves real-time performance, ideal for resource-constrained platforms like drones.

Keywords:
UAVevent cameranavigationvisual–inertial odometry

More Related Videos

Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine
07:05

Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine

Published on: October 27, 2016

9.2K
Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

1.3K

Related Experiment Videos

Last Updated: Jun 3, 2025

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field
06:52

An Inertial Measurement Unit Based Method to Estimate Hip and Knee Joint Kinematics in Team Sport Athletes on the Field

Published on: May 26, 2020

7.9K
Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine
07:05

Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine

Published on: October 27, 2016

9.2K
Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

1.3K

Area of Science:

  • Robotics
  • Computer Vision
  • Sensor Fusion

Background:

  • Indoor navigation is critical but challenging due to GNSS signal unavailability.
  • Event cameras offer high dynamic range and low latency, suitable for indoor environments.

Purpose of the Study:

  • To develop an efficient event-based visual-inertial odometry approach for precise indoor navigation.
  • To reduce computational overhead using adaptive event accumulation and selective keyframe updates.

Main Methods:

  • Fusing event data, standard image frames, and inertial measurements.
  • Detecting and tracking features in standard images, using accumulated events for inter-frame tracking.
  • Estimating sensor states by fusing IMU measurements and feature tracks.

Main Results:

  • Achieved substantial reductions in mean positional error (up to 50% on x-axis) and RMSE (up to 47% on y-axis) compared to U-SLAM in simulations.
  • Demonstrated real-time performance with 5-10 ms latency per event batch and 10-20 ms for frame updates.
  • Validated on both simulated and real-world datasets.

Conclusions:

  • The proposed approach offers a robust solution for UAV indoor navigation.
  • Event-based visual-inertial odometry is a promising technique for precise and efficient indoor localization.
  • The method is suitable for resource-constrained platforms.