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

Vision01:24

Vision

54.8K
Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.
54.8K
Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

813
Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
813
Association Areas of the Cortex01:21

Association Areas of the Cortex

5.8K
Association areas are regions of the cerebral cortex that do not have a specific sensory or motor function. Instead, they integrate and interpret information from various sources to enable higher cognitive processes such as memory, learning, and decision-making. Some key association areas include the following:
Prefrontal Association Area: This area is located in the frontal lobe and is involved in planning, decision-making, and moderating social behavior. It connects with primary motor areas,...
5.8K
Visual System01:26

Visual System

645
Light enters the eye through the cornea, a transparent, dome-shaped surface covering the surface of the eyeball that helps to direct and focus incoming light. This light is then channeled toward the pupil, an adjustable opening whose size is controlled by the iris. The iris, a pigmented muscle, regulates the amount of light entering the eye by contracting or dilating the pupil, thereby ensuring optimal light levels for clear vision.
Once through the pupil, the light passes through the lens, a...
645

You might also read

Related Articles

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

Sort by
Same author

Periodic Molecular-Level Asymmetric Channels for Synergistical Purification of Iodide Wastewater and Osmotic Power Generation.

Journal of the American Chemical Society·2026
Same author

Spin-state regulation of high-entropy Ruddlesden-Popper perovskite oxides for efficient seawater electrolysis.

Nature communications·2026
Same author

W<sub>2</sub>N<sub>3</sub> nanodot/2D C<sub>3</sub>N<sub>4</sub> heterostructures with interfacial covalent bonding toward Pt-free photocatalytic hydrogen evolution.

Nanoscale·2026
Same author

Iodine-Based Electrolyte Chemistry Enabling Reversible Ca Metal Anodes.

JACS Au·2026
Same author

Stabilization of Single Metal Atoms on Graphitic Carbon Nitride: Synthetic Strategies and Emerging Applications.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Sequential-chain coupling over hierarchical click-sites enables highly selective urea electrosynthesis.

Nature communications·2026

Related Experiment Video

Updated: Aug 17, 2025

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

604

SLAM Back-End Optimization Algorithm Based on Vision Fusion IPS.

Yu Xia1, Jingdi Cheng1, Xuhang Cai1

  • 1School of Information Engineering, Yangzhou University, Yangzhou 225127, China.

Sensors (Basel, Switzerland)
|December 11, 2022
PubMed
Summary
This summary is machine-generated.

This study integrates an Indoor Positioning System (IPS) into Simultaneous Localization and Mapping (SLAM) to prevent cumulative drift in mobile robot navigation. The fused system achieves high localization accuracy without relying on loopback detection.

Keywords:
Indoor Positioning SystemSLAMback-end optimizationpositional trajectory

More Related Videos

Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders
05:49

Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders

Published on: November 1, 2024

885
Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development
13:01

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development

Published on: April 10, 2016

34.1K

Related Experiment Videos

Last Updated: Aug 17, 2025

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

604
Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders
05:49

Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders

Published on: November 1, 2024

885
Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development
13:01

Using Light Sheet Fluorescence Microscopy to Image Zebrafish Eye Development

Published on: April 10, 2016

34.1K

Area of Science:

  • Robotics
  • Computer Vision
  • Sensor Fusion

Background:

  • Simultaneous Localization and Mapping (SLAM) systems often suffer from cumulative drift when relying solely on visual odometry.
  • Classical visual SLAM methods depend on loopback detection for trajectory correction, which is not always feasible.
  • Uncorrected drift limits the precision and reliability of mobile robot localization in indoor environments.

Purpose of the Study:

  • To mitigate the cumulative drift problem in visual SLAM systems.
  • To enhance the localization accuracy and robustness of mobile robots.
  • To introduce a novel approach by fusing an Indoor Positioning System (IPS) with SLAM.

Main Methods:

  • Integrated an Indoor Positioning System (IPS) into the back-end optimization of a visual SLAM framework.
  • Employed a two-label orientation method to estimate mobile robot pose, including position and heading angle.
  • Utilized pose information from IPS as an absolute constraint for trajectory optimization.

Main Results:

  • The fused SLAM algorithm achieved localization accuracy between 0.02 m and 0.03 m on the AUTOLABOR mobile robot.
  • The system demonstrated effective mitigation of cumulative drift, even without loopback detection.
  • The enhanced SLAM system meets stringent indoor localization accuracy requirements.

Conclusions:

  • Fusing IPS with SLAM effectively addresses the cumulative drift issue in visual odometry-based systems.
  • The proposed method provides global constraints for robust trajectory optimization.
  • This approach significantly improves the reliability of indoor mobile robot navigation.