Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Three-Dimensional Force System:Problem Solving

Three-Dimensional Force System:Problem Solving

A three-dimensional force system refers to a scenario in which three forces act simultaneously in three different directions. This type of problem is commonly encountered in physics and engineering, where it is necessary to calculate the resultant force on the system, which can then be used to predict or analyze the behavior of the object or structure under consideration.
To solve a three-dimensional force system, first resolve each force into its respective scalar components. Do this using...

Absolute Motion Analysis- General Plane Motion

Absolute Motion Analysis- General Plane Motion

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...

Relative Motion Analysis using Rotating Axes-Problem Solving

Relative Motion Analysis using Rotating Axes-Problem Solving

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...

Equation of Motion: General Plane motion - Problem Solving

Equation of Motion: General Plane motion - Problem Solving

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...

Two-Dimensional Force System: Problem Solving

Two-Dimensional Force System: Problem Solving

Solving problems related to two-dimensional force systems is an essential aspect of mechanics and engineering. By applying the principles of vector analysis and force equilibrium, one can determine the effect of multiple forces acting on an object in a two-dimensional space.
The first step to solving a two-dimensional force system problem is to draw a free-body diagram of the object under consideration. This diagram helps identify all the external forces acting on the object, including their...

Types of Global Positioning System Surveys

Types of Global Positioning System Surveys

GPS surveying methods vary in application, accuracy, and data collection techniques, catering to diverse surveying and mapping needs. Static GPS, kinematic GPS, and real-time kinematic (RTK) surveying are widely used. Each technique offers distinct advantages.Static GPS involves placing one receiver at a known reference point and another at the target point. It collects exact positional data by observing multiple satellite ranges over an extended period, achieving centimeter-level accuracy for...

You might also read

Related Articles

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

Sort by

Same author

Using Nanoindentation to Characterize the Mechanical and Creep Properties of Shale: Load and Loading Strain Rate Effects.

ACS omega·2022

Same author

Different Hemodynamic Characteristics and Resulting in Different Risks of Rupture Between Wide-Neck and Narrow-Neck Aneurysms.

Frontiers in neurology·2022

Same author

Interplay between quantum anomalous Hall effect and magnetic skyrmions.

Proceedings of the National Academy of Sciences of the United States of America·2022

Same author

The Ag-promoted α-C-H arylation of alcohols.

RSC advances·2022

Same author

Clinicopathological study of gastric schwannoma and review of related literature.

BMC surgery·2022

Same author

[Determination of 44 foodborne stimulants and 6 progestogens in meat by QuEChERS and ultra-performance liquid chromatography-tandem mass spectrometry].

Se pu = Chinese journal of chromatography·2022

Search research articles

Related Experiment Video

Updated: Jan 10, 2026

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

Multi-Strategy Improved POA for Global Optimization Problems and 3D UAV Path Planning.

Rui Zhang^1,2, Jingbo Zhan³, Jianfeng Wang⁴

¹School of Engineering Science, Shandong Xiehe University, Jinan 250107, China.

Biomimetics (Basel, Switzerland)

|November 26, 2025

Summary

This summary is machine-generated.

A new Multi-strategy Enhanced Pelican Optimization Algorithm (MIPOA) improves drone path planning by enhancing initial populations and accelerating convergence. This advanced algorithm ensures efficient and safe drone missions, overcoming limitations of existing methods.

Keywords:

3D UAV path planning IEEE CEC2017 intelligent optimization algorithm pelican optimization algorithm

More Related Videos

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

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

Published on: October 14, 2017

Related Experiment Videos

Last Updated: Jan 10, 2026

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Published on: December 9, 2012

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

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

Published on: October 14, 2017

Area of Science:

Robotics and Automation
Artificial Intelligence
Aerospace Engineering

Background:

Drone technology is crucial for smart manufacturing and the low-altitude economy.
Path planning is a core challenge impacting drone efficiency and safety.
Existing algorithms often require extensive data or get stuck in local optima.

Purpose of the Study:

Introduce a novel algorithm for Unmanned Aerial Vehicle (UAV) path planning.
Address limitations of current path planning methods, such as local optima and data dependency.
Enhance the efficiency, safety, and robustness of drone missions.

Main Methods:

Developed a Multi-strategy Enhanced Pelican Optimization Algorithm (MIPOA).
Implemented a hybrid initialization combining low-discrepancy sequences and heuristic refinement.
Incorporated subgroup mean-guided updating and a random reinitialization boundary mechanism.

Main Results:

MIPOA demonstrated superior optimization capability compared to eleven benchmark metaheuristics on the CEC2017 test suite.
Statistical analyses confirmed the algorithm's enhanced performance.
Successfully applied MIPOA to 3D UAV path planning in realistic threat scenarios.

Conclusions:

MIPOA offers a robust and adaptable solution for UAV path planning.
The algorithm effectively overcomes challenges like local optima and premature convergence.
MIPOA ensures successful mission completion in complex, dynamic environments.