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

Buoyancy and Stability for Submerged and Floating Bodies01:11

Buoyancy and Stability for Submerged and Floating Bodies

2.4K
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...
2.4K
Uniform Depth Channel Flow: Problem Solving01:18

Uniform Depth Channel Flow: Problem Solving

394
To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
394
Hierarchy of Motor Control01:18

Hierarchy of Motor Control

5.7K
The hierarchy of motor control refers to the different levels of organization and processing involved in controlling movement in the body. These levels range from higher cortical areas involved in planning and decision-making to lower spinal cord reflexes that respond automatically to external stimuli.
5.7K
One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

743
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...
743
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

652
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...
652
Absolute Motion Analysis- General Plane Motion01:24

Absolute Motion Analysis- General Plane Motion

468
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...
468

You might also read

Related Articles

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

Sort by
Same author

Bilevel Optimization-Based Time-Optimal Path Planning for AUVs.

Sensors (Basel, Switzerland)·2018
Same author

Association of maternal serum copper during early pregnancy with the risk of spontaneous preterm birth: A nested case-control study in China.

Environment international·2018
Same author

Automatic Assessment of Full Left Ventricular Coverage in Cardiac Cine Magnetic Resonance Imaging with Fisher Discriminative 3D CNN.

IEEE transactions on bio-medical engineering·2018
Same author

Diphenyl Ethers from a Marine-Derived <i>Aspergillus sydowii</i>.

Marine drugs·2018
Same author

In situ determination of trace elements in melt inclusions using laser ablation inductively coupled plasma sector field mass spectrometry.

Rapid communications in mass spectrometry : RCM·2018
Same author

A genetic variant in LINGO2 contributes to the risk of gestational diabetes mellitus in a Chinese population.

Journal of cellular physiology·2018

Related Experiment Video

Updated: Dec 29, 2025

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

12.1K

Path Following Based on Waypoints and Real-Time Obstacle Avoidance Control of an Autonomous Underwater Vehicle.

Xuliang Yao1, Xiaowei Wang1,2, Feng Wang1

  • 1College of Automation, Harbin Engineering University, Harbin 150001, China.

Sensors (Basel, Switzerland)
|February 7, 2020
PubMed
Summary

This study introduces an improved control method for autonomous underwater vehicles (AUVs) using model predictive control (MPC) and sliding mode control (SMC). The method enhances path following and obstacle avoidance while reducing energy consumption.

Keywords:
AUVMPCSMCobstacle avoidancepath following

More Related Videos

Quantitatively Measuring In situ Flows using a Self-Contained Underwater Velocimetry Apparatus SCUVA
09:22

Quantitatively Measuring In situ Flows using a Self-Contained Underwater Velocimetry Apparatus SCUVA

Published on: October 31, 2011

13.4K
Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish
10:56

Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish

Published on: March 6, 2014

12.9K

Related Experiment Videos

Last Updated: Dec 29, 2025

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
11:53

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

Published on: October 14, 2017

12.1K
Quantitatively Measuring In situ Flows using a Self-Contained Underwater Velocimetry Apparatus SCUVA
09:22

Quantitatively Measuring In situ Flows using a Self-Contained Underwater Velocimetry Apparatus SCUVA

Published on: October 31, 2011

13.4K
Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish
10:56

Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish

Published on: March 6, 2014

12.9K

Area of Science:

  • Robotics
  • Control Systems
  • Ocean Engineering

Background:

  • Underactuated autonomous underwater vehicles (AUVs) require advanced control for navigation.
  • Path following and obstacle avoidance are critical for AUV mission success.
  • Existing methods face challenges with model uncertainty and control input saturation.

Purpose of the Study:

  • To develop a robust control strategy for 3D straight-line path following and obstacle avoidance in underactuated AUVs.
  • To improve tracking accuracy and real-time obstacle avoidance capabilities.
  • To address dynamic model uncertainties and control input limitations.

Main Methods:

  • Design of kinematic controller using Line-of-Sight (LOS) guidance and Model Predictive Control (MPC).
  • Integration of an obstacle avoidance penalty item based on sensor data.
  • Application of Sliding Mode Control (SMC) for dynamic control, addressing model uncertainty and input saturation.

Main Results:

  • The improved MPC and SMC method demonstrated superior path-following performance, especially near waypoints.
  • Effective real-time obstacle avoidance of unknown obstacles was achieved.
  • Significant reduction in Mean Square Error (MSE) and rudder angle saturation rate compared to traditional LOS methods.

Conclusions:

  • The proposed control method enhances AUV tracking quality and obstacle avoidance.
  • It effectively mitigates dynamic model uncertainties and control input saturation.
  • The approach promotes system stability and energy efficiency in AUV operations.