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

Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

106
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
106
One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

488
In mechanical engineering, one-degree-of-freedom systems form the basis of a wide range of electrical and mechanical components. Using these models, engineers can predict the behavior of various parts in a larger system, which gives them insight into how different forces interact with each other.
A one-degree-of-freedom system is defined by an independent variable that determines its state and behavior. One example of a one-degree-of-freedom system is a simple harmonic oscillator, such as a...
488
Errors in Global Positioning System01:26

Errors in Global Positioning System

45
Global Positioning System (GPS) technology has revolutionized navigation and positioning, but its accuracy is often compromised by various errors. These errors, stemming from environmental, satellite, and receiver-related factors, require careful mitigation to ensure reliable performance across applications.Atmospheric ErrorsGPS signals travel through the Earth’s ionosphere and troposphere, introducing delays which affect accuracy. The ionosphere is strongly influenced by charged particles,...
45
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

402
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...
402
Inertial Frames of Reference01:03

Inertial Frames of Reference

7.1K
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...
7.1K
Introduction to Global Positioning System01:30

Introduction to Global Positioning System

60
The Global Positioning System (GPS) revolutionized positioning on Earth, providing precise location data through satellite ranging. The GPS system was developed in 1978 by the U.S. Department of Defense  for military use, and it became available for civilian applications in 1983, transforming fields including navigation, fleet management, and time synchronization for telecommunications systems.GPS consists of satellites in medium Earth orbit, about 20,200 kilometers above the surface,...
60

You might also read

Related Articles

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

Sort by
Same author

Clinical trials of GPE-based muscle support algorithm for robotic hip exoskeleton: a pilot study.

Scientific reports·2025
Same author

<i>Luffa cylindrica</i>-inspired powerless micropump: long-term, high-flow operation and energy-generation application.

Lab on a chip·2025
Same author

An Enhanced Indoor Three-Dimensional Localization System with Sensor Fusion Based on Ultra-Wideband Ranging and Dual Barometer Altimetry.

Sensors (Basel, Switzerland)·2024
Same author

Effects of Laser Scanning Strategy on Bending Behavior and Microstructure of DP980 Steel.

Materials (Basel, Switzerland)·2024
Same author

Construction of Monolayer Ti<sub>3</sub>C<sub>2</sub>T<sub>x</sub> MXene on Nickel Foam under High Electrostatic Fields for High-Performance Supercapacitors.

Nanomaterials (Basel, Switzerland)·2024
Same author

The effect of training using an upper limb rehabilitation robot (HEXO-UR30A) in chronic stroke patients: A randomized controlled trial.

Medicine·2023

Related Experiment Video

Updated: Jul 2, 2025

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions
09:46

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

Published on: May 10, 2012

12.7K

A Planar Multi-Inertial Navigation Strategy for Autonomous Systems for Signal-Variable Environments.

Wenbin Dong1,2, Cheng Lu2, Le Bao1

  • 1Department of Mechatronics Engineering, Hanyang University, Ansan 15588, Republic of Korea.

Sensors (Basel, Switzerland)
|February 24, 2024
PubMed
Summary

A new multi-inertial navigation system (M-INSs) improves mobile robot dynamic positioning by integrating multiple INS units and an extended Kalman filter (EKF). This system reduces positioning errors by over 60% for enhanced robotic navigation accuracy.

Keywords:
EKFINSautonomous navigationlocalizationmobile robot

More Related Videos

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants
06:28

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

Published on: August 26, 2018

6.0K
Author Spotlight: Investigating the Effects of Mind-Body-Movement Practices on Brain Function
06:17

Author Spotlight: Investigating the Effects of Mind-Body-Movement Practices on Brain Function

Published on: January 26, 2024

1.9K

Related Experiment Videos

Last Updated: Jul 2, 2025

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions
09:46

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

Published on: May 10, 2012

12.7K
A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants
06:28

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

Published on: August 26, 2018

6.0K
Author Spotlight: Investigating the Effects of Mind-Body-Movement Practices on Brain Function
06:17

Author Spotlight: Investigating the Effects of Mind-Body-Movement Practices on Brain Function

Published on: January 26, 2024

1.9K

Area of Science:

  • Robotics
  • Navigation Systems
  • Sensor Fusion

Background:

  • Traditional single inertial navigation systems (INSs) suffer from cumulative sensor errors, especially under dynamic conditions, limiting mobile robot precision.
  • Precise dynamic positioning is crucial for advanced mobile robot applications like autonomous driving and disaster response.

Purpose of the Study:

  • To develop and validate a multi-inertial navigation system (M-INSs) algorithm to overcome the limitations of single INS units for dynamic positioning.
  • To significantly enhance the positioning accuracy and stability of mobile robots operating in dynamic environments.

Main Methods:

  • A novel algorithm integrating multiple INS units in a planar configuration was developed, using fixed inter-unit distances as invariant constraints.
  • An extended Kalman filter (EKF) was employed for sensor data fusion and state estimation to improve positioning accuracy.
  • Dynamic experimental validation was performed to assess the performance of the proposed 3INS EKF algorithm against individual INS units.

Main Results:

  • The multi-INS EKF algorithm demonstrated a marked improvement in positioning accuracy and stability compared to individual INS units.
  • Positioning errors were significantly reduced, achieving an average accuracy enhancement rate exceeding 60%.
  • The system proved effective in mitigating cumulative sensor errors inherent in traditional INS under dynamic conditions.

Conclusions:

  • The developed M-INSs, utilizing an EKF, offers a robust solution for precise dynamic positioning of mobile robots.
  • This advancement provides a critical improvement for high-precision mobile robot applications, including autonomous driving and search and rescue.
  • The study opens new research avenues for enhancing robotic navigation systems through multi-sensor integration and advanced filtering techniques.