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

PD Controller: Design01:26

PD Controller: Design

322
In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
322
Rolling Resistance: Problem Solving01:17

Rolling Resistance: Problem Solving

420
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...
420
Root-Locus Method01:19

Root-Locus Method

202
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...
202
Direct Motor Pathways01:11

Direct Motor Pathways

2.3K
The direct motor pathways, also known as the pyramidal tracts, are a group of neural pathways that originate in the brain and descend through the spinal cord. They control the voluntary movement of the body. There are two major direct motor pathways: the corticospinal and the corticobulbar tracts.
The corticospinal tract is responsible for the voluntary movement of the limbs and trunk. It originates in the cerebral cortex of the brain and descends through the cerebrum's internal capsule and...
2.3K
Indirect Motor Pathways01:22

Indirect Motor Pathways

1.6K
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...
1.6K
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

441
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...
441

You might also read

Related Articles

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

Sort by
Same author

Effects of semantic distance and metaphorical constituent position on L2 noun-noun metaphor processing: an ERP study.

Brain and language·2026
Same author

Simultaneous degradation of aflatoxin B<sub>1</sub>, zearalenone, and deoxynivalenol by <i>Trametes versicolor</i> laccases.

Frontiers in nutrition·2026
Same author

Leveraging whole-genome sequencing for microbial contamination tracking and risk assessment in pharmaceutical manufacturing.

Frontiers in microbiology·2026
Same author

Central Venous Catheter for Treating Pseudomeningocele Compressing the Spinal Cord After Thoracic Ossification Surgery: Case Series.

Orthopaedic surgery·2026
Same author

Liquid Coordination Environment-Induced Liquid-Like Metal Behavior: Mobile Single-Atom Copper Catalytic Centers.

Journal of the American Chemical Society·2026
Same author

Gut-liver axis dysregulation in colitis underlies structure-dependent pharmacokinetics of a traditional Chinese medicine.

Pharmacological research·2026

Related Experiment Video

Updated: Aug 29, 2025

Using a Virtual Reality Walking Simulator to Investigate Pedestrian Behavior
06:38

Using a Virtual Reality Walking Simulator to Investigate Pedestrian Behavior

Published on: June 9, 2020

4.9K

Smart Vehicle Path Planning Based on Modified PRM Algorithm.

Qiongqiong Li1, Yiqi Xu1, Shengqiang Bu1

  • 1College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, China.

Sensors (Basel, Switzerland)
|September 9, 2022
PubMed
Summary
This summary is machine-generated.

This study enhances path planning for smart vehicles by improving the Probabilistic Roadmap Method (PRM). The modified PRM offers faster roadmap construction and more efficient path planning with shorter path lengths.

Keywords:
collision detectionpath smoothingprobabilistic roadmap algorithmpseudo-random samplingsmart vehicle

More Related Videos

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

11.8K
Operation of the Collaborative Composite Manufacturing CCM System
10:09

Operation of the Collaborative Composite Manufacturing CCM System

Published on: October 1, 2019

6.7K

Related Experiment Videos

Last Updated: Aug 29, 2025

Using a Virtual Reality Walking Simulator to Investigate Pedestrian Behavior
06:38

Using a Virtual Reality Walking Simulator to Investigate Pedestrian Behavior

Published on: June 9, 2020

4.9K
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

11.8K
Operation of the Collaborative Composite Manufacturing CCM System
10:09

Operation of the Collaborative Composite Manufacturing CCM System

Published on: October 1, 2019

6.7K

Area of Science:

  • Robotics
  • Artificial Intelligence
  • Computer Science

Background:

  • Path planning is crucial for mobile smart vehicles navigating complex environments.
  • Sampling-based planners like the Probabilistic Roadmap Method (PRM) are widely used but have limitations.
  • Existing PRM methods suffer from low efficiency, poor roadmap reuse, and suboptimal sampling point selection.

Purpose of the Study:

  • To address the limitations of traditional PRM algorithms for smart vehicle path planning.
  • To develop an optimized PRM strategy for enhanced efficiency and path quality.
  • To improve roadmap construction speed and path planning performance.

Main Methods:

  • Designed a pseudo-random sampling strategy using the main spatial axis as a reference.
  • Optimized sampling point generation, removed redundant points, and implemented a distance threshold.
  • Employed a two-way incremental collision detection method and optimized collision check calls.
  • Utilized Bessel curves for path smoothing, extracting key points as discrete control points.

Main Results:

  • The modified PRM demonstrated significant improvements in roadmap construction speed.
  • Enhanced efficiency in path planning and reduction in overall path length were observed.
  • Validation using MATLAB and ROS confirmed the algorithm's effectiveness.

Conclusions:

  • The modified PRM algorithm offers superior performance compared to the basic PRM.
  • The proposed enhancements lead to faster and more efficient path planning for smart vehicles.
  • Smoothed paths generated by the modified PRM are more suitable for real-world driving conditions.