Jove
Visualize
Contact Us

Related Concept Videos

Buoyancy and Stability for Submerged and Floating Bodies01:11

Buoyancy and Stability for Submerged and Floating Bodies

2.3K
In fluid mechanics, buoyancy and stability are key concepts for understanding the behavior of submerged and floating bodies. When a stationary body is fully or partially submerged in a fluid, the fluid exerts a force on the body known as the buoyant force. This force acts vertically upward through a point called the center of buoyancy, which is the center of the displaced fluid volume. According to Archimedes' principle, the magnitude of the buoyant force is equal to the weight of the fluid...
2.3K
Buoyancy00:59

Buoyancy

11.5K
When an object is placed in a fluid, it either floats or sinks. All objects in a fluid experience a buoyant force. For example, a metal ball sinks, while a rubber ball floats. Similarly, a submarine can sink and float by adjusting its buoyancy.  The concept of buoyancy raises several interesting questions. For instance, where does this buoyant force come from? How much buoyant force is required to make an object sink or float? Do objects that sink get any support at all from the...
11.5K
Anchoring Junctions01:03

Anchoring Junctions

4.4K
Anchoring junctions are multiprotein complexes that help cells connect to other cells and the extracellular matrix. Anchoring junctions are present on the lateral and basal surfaces of cells, providing strong and flexible connections. Focal adhesions are often formed due to cell interactions with the ECM substrata, which initiate signal transduction via kinase cascades and other mechanisms. Together, they provide stability and tissue integrity. There are three types of anchoring junctions:...
4.4K

You might also read

Related Articles

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

Sort by
Same author

Vision driven trailer loading for autonomous surface vehicles in dynamic environments.

Frontiers in robotics and AI·2025
Same author

Dynamic Obstacle Avoidance for USVs Using Cross-Domain Deep Reinforcement Learning and Neural Network Model Predictive Controller.

Sensors (Basel, Switzerland)·2023
Same author

ROSEBUD: A Deep Fluvial Segmentation Dataset for Monocular Vision-Based River Navigation and Obstacle Avoidance.

Sensors (Basel, Switzerland)·2022
Same author

Robust ASV Navigation Through Ground to Water Cross-Domain Deep Reinforcement Learning.

Frontiers in robotics and AI·2021
Same author

Compact Quantum Magnetometer System on an Agile Underwater Glider.

Sensors (Basel, Switzerland)·2021
Same author

Reinforcement Learning-Based Multi-AUV Adaptive Trajectory Planning for Under-Ice Field Estimation.

Sensors (Basel, Switzerland)·2018
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: Nov 10, 2025

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus
05:57

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus

Published on: April 8, 2019

7.0K

Underwater Docking Approach and Homing to Enable Persistent Operation.

Brian R Page1, Reeve Lambert1, Jalil Chavez-Galaviz1

  • 1School of Mechanical Engineering, Purdue University, West Lafayette, IN, United States.

Frontiers in Robotics and AI
|April 1, 2021
PubMed
Summary

Marine robots face energy challenges. This study introduces a navigation algorithm for reliable underwater docking, enabling persistent autonomous underwater vehicle operations.

Keywords:
autonomous underwater dockingautonomous underwater vehiclemarine robot navigationmarine roboticsunderwater docking techniqueunderwater robot

More Related Videos

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
09:19

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging

Published on: April 18, 2025

1.1K
Coral Reef Arks: An In Situ Mesocosm and Toolkit for Assembling Reef Communities
07:59

Coral Reef Arks: An In Situ Mesocosm and Toolkit for Assembling Reef Communities

Published on: January 6, 2023

3.8K

Related Experiment Videos

Last Updated: Nov 10, 2025

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus
05:57

Long-term Video Tracking of Cohoused Aquatic Animals: A Case Study of the Daily Locomotor Activity of the Norway Lobster Nephrops norvegicus

Published on: April 8, 2019

7.0K
Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging
09:19

Measuring the Structure, Composition, and Change of Underwater Environments with Large-area Imaging

Published on: April 18, 2025

1.1K
Coral Reef Arks: An In Situ Mesocosm and Toolkit for Assembling Reef Communities
07:59

Coral Reef Arks: An In Situ Mesocosm and Toolkit for Assembling Reef Communities

Published on: January 6, 2023

3.8K

Area of Science:

  • Robotics
  • Marine Engineering
  • Navigation Systems

Background:

  • Energy sustainability is a major limitation for marine robot deployment.
  • Propeller-driven autonomous underwater vehicles (AUVs) consume significant energy.
  • Autonomous recharging via underwater docking stations offers a solution for persistent AUV operations.

Purpose of the Study:

  • To present an integrated navigational algorithm for reliable underwater docking of AUVs.
  • To enable persistent undersea operations through autonomous docking and retasking.

Main Methods:

  • Dynamically re-planning Dubins paths for efficient trajectories from current position to terminal homing.
  • Utilizing integral line of sight control for path following.
  • Employing a light tracking algorithm for final homing into the dock.
  • Implementing re-attempt strategies for failed docking scenarios.

Main Results:

  • The approach phase successfully reached the target handoff within 2m in all 48 tests.
  • The terminal homing phase achieved approximately 70% accuracy (12/17 tests) with up to 5m offsets.
  • Re-attempts significantly increase the likelihood of successful docking.

Conclusions:

  • The developed algorithm facilitates reliable underwater docking for AUVs.
  • This technology, combined with advancements in docking stations and communication, enables persistent undersea operations.
  • The system is robust and capable of handling dynamic ocean environments.