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

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...

You might also read

Related Articles

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

Sort by

Same author

Enhancing medical Q&A systems with multimodal knowledge graphs and dual-layer attention mechanisms.

PloS one·2026

Same author

A case of lung cancer-associated pulmonary embolism mimicking Kimura disease: a case report.

Journal of medical case reports·2026

Same author

Both of coagulopathy and neutrophil extracellular trap markers are associated with poor prognosis of dabie bandavirus infection.

Clinica chimica acta; international journal of clinical chemistry·2026

Same author

Multi-level information fusion for explainable diagnosis of melanoma using dermoscopic images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society·2026

Same author

Magnetostrictive mechanical frequency combs.

Nature communications·2025

Same author

Nitrogen ion implantation significantly enhances the tribological properties and corrosion resistance of aluminum-lithium alloy.

Annals of the New York Academy of Sciences·2025

Search research articles

Related Experiment Video

Updated: Oct 5, 2025

Operation of the Collaborative Composite Manufacturing CCM System

Operation of the Collaborative Composite Manufacturing CCM System

Published on: October 1, 2019

Path planning of a manipulator based on an improved P_RRT* algorithm.

Junhui Yi¹, Qingni Yuan¹, Ruitong Sun¹

¹Key Laboratory of Modern Manufacturing Technology, Ministry of Education, West Campus, Guizhou University, Huaxi District, Guiyang, Guizhou China.

Complex & Intelligent Systems

|January 26, 2022

Summary

This summary is machine-generated.

This study introduces an improved potential function-based rapidly exploring random tree star (P_RRT*) algorithm to enhance path planning for manipulators. The enhanced method accelerates search efficiency and generates smoother, less tortuous paths.

Keywords:

Improved P_RRT* algorithm Manipulator Nearest neighbour node selection Path planning Two expansions

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

Compensatory Limb Use and Behavioral Assessment of Motor Skill Learning Following Sensorimotor Cortex Injury in a Mouse Model of Ischemic Stroke

Compensatory Limb Use and Behavioral Assessment of Motor Skill Learning Following Sensorimotor Cortex Injury in a Mouse Model of Ischemic Stroke

Published on: July 10, 2014

Related Experiment Videos

Last Updated: Oct 5, 2025

Operation of the Collaborative Composite Manufacturing CCM System

Operation of the Collaborative Composite Manufacturing CCM System

Published on: October 1, 2019

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

Compensatory Limb Use and Behavioral Assessment of Motor Skill Learning Following Sensorimotor Cortex Injury in a Mouse Model of Ischemic Stroke

Compensatory Limb Use and Behavioral Assessment of Motor Skill Learning Following Sensorimotor Cortex Injury in a Mouse Model of Ischemic Stroke

Published on: July 10, 2014

Area of Science:

Robotics
Artificial Intelligence
Computational Geometry

Background:

The potential function-based rapidly exploring random tree star (P_RRT*) algorithm suffers from slow convergence and low search efficiency.
Path planning for manipulators in 3D space requires efficient and reliable algorithms.

Purpose of the Study:

To propose an improved P_RRT* algorithm for manipulator path planning in three-dimensional space.
To enhance the convergence speed and search efficiency of existing P_RRT* methods.

Main Methods:

A novel approach employing potential function-based random sampling and a dual-expansion strategy (goal-biased and rectangular area sampling).
Incorporation of parent node reselection, redundant node deletion, and maximum curvature constraints for path optimization.
Utilizing Bezier curves for trajectory fitting to generate smooth manipulator paths.

Main Results:

The improved P_RRT* algorithm demonstrated significantly enhanced search efficiency and faster convergence.
Generated paths exhibited reduced tortuosity due to redundant node deletion and curvature constraints.
Experimental validation in Python and ROS confirmed the algorithm's effectiveness and superiority over existing methods.

Conclusions:

The proposed improved P_RRT* algorithm offers a superior solution for manipulator path planning in 3D environments.
The method effectively addresses the limitations of traditional P_RRT* algorithms, providing faster and smoother path generation.
The successful experimental verification highlights the practical applicability and performance advantages of the enhanced algorithm.