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
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

648
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...
648
Root-Locus Method01:19

Root-Locus Method

402
A cruise control system in a car is designed to maintain a specified speed automatically by adjusting the gas pedal. The system continuously measures the vehicle's speed and makes fine adjustments to the pedal to achieve this goal. The root locus method is particularly useful for understanding how the cruise control system's behavior changes under varying conditions, such as when the car goes uphill, downhill, or faces strong wind resistance.
This system can be represented by a block...
402
Rolling Resistance: Problem Solving01:17

Rolling Resistance: Problem Solving

724
Rolling resistance, also known as rolling friction, is the force that resists the motion of a rolling object, such as a wheel, tire, or ball, when it moves over a surface. It is caused by the deformation of the object and the surface in contact with each other, as well as other factors like internal friction, hysteresis, and energy losses within the materials. Rolling resistance opposes the object's motion, requiring additional energy to overcome it and maintain movement. In practical...
724
Equation of Motion: General Plane motion - Problem Solving01:16

Equation of Motion: General Plane motion - Problem Solving

432
Consider a lawn roller with a mass of 100 kg, a radius of 0.2 meters, and a radius of gyration of 0.15 meters. A force of 200 N is applied to this roller, angled at 60 degrees from the horizontal plane. What will be the angular acceleration of the lawn roller?
The friction between the roller and the ground is characterized by two coefficients. The static friction coefficient is 0.15, while the kinetic friction coefficient is 0.1. These values are crucial in understanding the interaction between...
432
Indirect Motor Pathways01:22

Indirect Motor Pathways

2.9K
The indirect motor or extrapyramidal pathways originate in the brainstem, the lower portion of the brain that connects it to the spinal cord. They consist of several distinct tracts, each with specialized functions. The four main tracts of the indirect motor pathways are the vestibulospinal tract, the reticulospinal tract, the tectospinal tract, and the rubrospinal tract.
The vestibulospinal tract originates in the vestibular nuclei of the brainstem. The vestibular system detects changes in...
2.9K

You might also read

Related Articles

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

Sort by
Same author

A New Auto-Regressive Multi-Variable Modified Auto-Encoder for Multivariate Time-Series Prediction: A Case Study with Application to COVID-19 Pandemics.

International journal of environmental research and public health·2024
Same author

Complete holography-based system for the identification of microparticles in water samples.

Journal of microscopy·2023
Same author

COVID-19 Patterns in Araraquara, Brazil: A Multimodal Analysis.

International journal of environmental research and public health·2023
Same author

Robotics Research Growth in Latin America: Topical Collection on LARS 2020.

Journal of intelligent & robotic systems·2023
Same author

Improved Behavioral Box and Sensing Techniques for Analysis of Tactile Discrimination Tasks in Rodents.

Sensors (Basel, Switzerland)·2023
Same author

National Holidays and Social Mobility Behaviors: Alternatives for Forecasting COVID-19 Deaths in Brazil.

International journal of environmental research and public health·2021

Related Experiment Video

Updated: Dec 26, 2025

Designing and Implementing Nervous System Simulations on LEGO Robots
10:34

Designing and Implementing Nervous System Simulations on LEGO Robots

Published on: May 25, 2013

15.5K

High-Level Path Planning for an Autonomous Sailboat Robot Using Q-Learning.

Andouglas Gonçalves da Silva Junior1,2, Davi Henrique Dos Santos1, Alvaro Pinto Fernandes de Negreiros1

  • 1Universidade Federal do Rio Grande do Norte, DCA-CT-UFRN, Campus Universitario, Lagoa Nova, Natal, RN 59078-970, Brazil.

Sensors (Basel, Switzerland)
|March 15, 2020
PubMed
Summary

This study introduces a novel path planning algorithm for autonomous sailboats, utilizing Q-Learning to navigate complex routes safely and efficiently, even in challenging wind conditions.

Keywords:
ASVQ-LearningUSVautonomous sailboatgreen roboticsmobile roboticspath planning

More Related Videos

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

10.7K
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

Related Experiment Videos

Last Updated: Dec 26, 2025

Designing and Implementing Nervous System Simulations on LEGO Robots
10:34

Designing and Implementing Nervous System Simulations on LEGO Robots

Published on: May 25, 2013

15.5K
Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
11:18

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks

Published on: March 2, 2015

10.7K
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

Area of Science:

  • Robotics
  • Artificial Intelligence
  • Marine Engineering

Background:

  • Path planning for wind-propelled sailboat robots presents significant challenges due to complex kinematics and dynamics.
  • Existing methods often require manual input or struggle with dynamic environmental factors like wind direction.

Purpose of the Study:

  • To develop a robust global path planning algorithm for the N-Boat sailboat robot.
  • To enable autonomous navigation between start and target points while ensuring safety and efficiency.

Main Methods:

  • A two-layer approach: global path generation and local trajectory execution.
  • Utilized Q-Learning, a reinforcement learning technique, with a custom reward matrix.
  • Algorithm accounts for wind direction and the 'dead zone' using adaptive actions.

Main Results:

  • Generated feasible sailing routes, including straight and zigzag paths, considering wind conditions.
  • Ensured sailboat safety and robustness by avoiding obstacles and borders.
  • Algorithm demonstrated potential for long-duration autonomous sailing based solely on defined start and target points.

Conclusions:

  • The developed global path planner, combined with existing local planners, facilitates the creation of fully autonomous sailboat robots.
  • The Q-Learning approach effectively addresses the complexities of wind-propelled navigation.
  • This work contributes to advancing autonomous marine systems.