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

Planar Rigid-Body Motion01:22

Planar Rigid-Body Motion

1.4K
Understanding the movement of a rigid body in planar motion involves recognizing that every particle within this body is traversing a path that maintains a consistent distance from a specific plane. This concept is fundamental in the study of physics and mechanical engineering, and it allows us to comprehend better how objects move in space.
Planar motion is typically divided into three distinct categories. The first is rectilinear translation, demonstrated by a subway train that moves along...
1.4K
Absolute Motion Analysis- General Plane Motion01:24

Absolute Motion Analysis- General Plane Motion

681
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...
681
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

830
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...
830
Orthogonal Trajectories01:26

Orthogonal Trajectories

158
Orthogonal trajectories describe the geometric relationship between two families of curves that intersect each other at right angles. One illustrative case involves a family of parabolas that open sideways along the x-axis. These curves share a common shape but differ by a scaling parameter, resulting in a set of curves that all pass through the origin and widen at different rates.Determining Orthogonal TrajectoriesTo identify the orthogonal trajectories for these parabolas, the first step...
158
Relative Motion Analysis using Rotating Axes01:25

Relative Motion Analysis using Rotating Axes

1.0K
Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame.
However, to express the relative position of point B relative to point A, an additional frame of reference, denoted as x'y', is necessary. This additional frame not only translates but also rotates relative to the fixed frame, making it...
1.0K
One-Degree-of-Freedom System01:24

One-Degree-of-Freedom System

920
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...
920

You might also read

Related Articles

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

Sort by
Same author

Educational Outcomes of a Longitudinal Women's Reproductive Mental Health Elective in Psychiatry Residency Training.

Academic psychiatry : the journal of the American Association of Directors of Psychiatric Residency Training and the Association for Academic Psychiatry·2026
Same author

Implicit Bias and Recognition of Biases Among Vascular Surgeons.

The Journal of surgical research·2026
Same author

Current treatment options for perinatal depression.

Current opinion in obstetrics & gynecology·2026
Same author

Health Ratings and Unmet Transportation Needs in Indiana's Aged and Disabled Home and Community-Based Services Waiver Program.

Journal of aging & social policy·2025
Same author

Benchmarking the operation of quantum heuristics and Ising machines: scoring parameter setting strategies on optimization applications.

Quantum machine intelligence·2025
Same author

Implicit Racial Bias and Unintentional Harm in Vascular Care.

JAMA surgery·2025
Same journal

Tissue removal inside the beating heart using a robotically delivered metal MEMS tool.

The International journal of robotics research·2026
Same journal

Configuration identification of on-demand variable stiffness strain-limiting layers in zig-zag soft pneumatic actuators using deep learning methods.

The International journal of robotics research·2026
Same journal

A low-noise low-impedance powered knee prosthesis with direct ball screw drive and torque-sensitive actuation.

The International journal of robotics research·2026
Same journal

MUN-FRL: A Visual-Inertial-LiDAR Dataset for Aerial Autonomous Navigation and Mapping.

The International journal of robotics research·2025
Same journal

Certifiably optimal rotation and pose estimation based on the Cayley map.

The International journal of robotics research·2025
Same journal

A mathematical characterization of minimally sufficient robot brains.

The International journal of robotics research·2025
See all related articles

Related Experiment Video

Updated: Mar 23, 2026

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions
09:46

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

Published on: May 10, 2012

13.2K

Fast Marching Tree: a Fast Marching Sampling-Based Method for Optimal Motion Planning in Many Dimensions.

Lucas Janson1, Edward Schmerling2, Ashley Clark3

  • 1Department of Statistics, Stanford University.

The International Journal of Robotics Research
|March 23, 2016
PubMed
Summary
This summary is machine-generated.

We introduce the Fast Marching Tree algorithm (FMT*), a novel probabilistic sampling-based motion planning method. FMT* offers faster convergence to optimal solutions in high-dimensional spaces compared to existing algorithms like PRM* and RRT*.

More Related Videos

Operation of the Collaborative Composite Manufacturing CCM System
10:09

Operation of the Collaborative Composite Manufacturing CCM System

Published on: October 1, 2019

7.2K
A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery
09:41

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery

Published on: May 20, 2016

12.8K

Related Experiment Videos

Last Updated: Mar 23, 2026

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions
09:46

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

Published on: May 10, 2012

13.2K
Operation of the Collaborative Composite Manufacturing CCM System
10:09

Operation of the Collaborative Composite Manufacturing CCM System

Published on: October 1, 2019

7.2K
A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery
09:41

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery

Published on: May 20, 2016

12.8K

Area of Science:

  • Robotics and Artificial Intelligence
  • Motion Planning Algorithms
  • Computational Geometry

Background:

  • Complex motion planning problems in high-dimensional configuration spaces remain a significant challenge.
  • Existing algorithms such as Probabilistic Roadmaps (PRM*) and Rapidly-exploring Random Trees (RRT*) have limitations in convergence speed and optimality.
  • There is a need for more efficient and asymptotically optimal motion planning solutions.

Purpose of the Study:

  • To present a novel probabilistic sampling-based motion planning algorithm, the Fast Marching Tree (FMT*).
  • To demonstrate that FMT* is asymptotically optimal and converges faster than state-of-the-art methods.
  • To analyze FMT* using convergence in probability, enabling convergence rate bounds.

Main Methods:

  • Developed the Fast Marching Tree (FMT*) algorithm, employing a 'lazy' dynamic programming approach on probabilistically sampled points.
  • Grows a tree of paths outward in cost-to-arrive space, combining features of single-query and multiple-query algorithms.
  • Analyzed convergence using the notion of convergence in probability, deriving order O(n-1/) convergence rate bounds.

Main Results:

  • FMT* is proven to be asymptotically optimal and converges faster than PRM* and RRT*.
  • Achieved the first convergence rate bounds for optimal sampling-based motion planning: O(n-1/).
  • Numerical experiments confirm FMT* returns substantially better solutions, especially in high-dimensional spaces and with expensive collision-checking.

Conclusions:

  • The Fast Marching Tree (FMT*) algorithm represents a significant advancement in optimal sampling-based motion planning.
  • FMT* offers superior performance and convergence properties compared to existing methods, particularly in challenging environments.
  • The algorithm's theoretical analysis and empirical validation highlight its potential for complex robotics applications.