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 Experiment Videos

Using chaos to generate variations on movement sequences.

Elizabeth Bradley1, Joshua Stuart

  • 1Department of Computer Science, University of Colorado, Boulder, Colorado 80309-0430.

Chaos (Woodbury, N.Y.)
|June 5, 2003
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Healing Strides: The Effectiveness of a Combined Grief Group Counseling and 5K Race Training Intervention on Grief-Related Symptoms.

Omega·2026
Same author

CLEAR: Comparative Letter Examination and Analysis for Red Flags.

Journal of graduate medical education·2026
Same author

Inside Their Minds: A Multi-Institutional Exploration into the Decision-Making of Medical School Competency Committee Members.

Perspectives on medical education·2026
Same author

Coupled catastrophes in systems with bidirectional feedback.

Chaos (Woodbury, N.Y.)·2025
Same author

The United States Withdrawal From the World Health Organization: Implications and Challenges.

International journal of health policy and management·2025
Same author

Introduction to focus issue: Topics in nonlinear science.

Chaos (Woodbury, N.Y.)·2025
Same journal

Exploring mechanisms for reversal of flow in tunicate hearts.

Chaos (Woodbury, N.Y.)·2026
Same journal

State estimation in spatiotemporal chaos via low-rank StatFEM.

Chaos (Woodbury, N.Y.)·2026
Same journal

Universal response functions in driven dissipative tunneling dynamics.

Chaos (Woodbury, N.Y.)·2026
Same journal

A network-based approach to characterize the dynamics of the coupling field of thermoacoustic oscillators in annular geometry.

Chaos (Woodbury, N.Y.)·2026
Same journal

Data-driven soliton manifold approximations for dark and bright waves: Some prototypical 1D case examples.

Chaos (Woodbury, N.Y.)·2026
Same journal

Gap junction architecture and synchronization clusters in the thalamic reticular nuclei.

Chaos (Woodbury, N.Y.)·2026
See all related articles

This study introduces a novel chaotic symbol-sequence reordering technique to create variations in motion sequences. The method ensures variations are distinct yet aesthetically and mathematically similar to the original movement.

Area of Science:

  • Computational dynamics
  • Applied mathematics
  • Robotics and motion control

Background:

  • Predefined motion sequences, such as in dance or martial arts, lack inherent variability.
  • Generating meaningful variations in these sequences often requires complex manual intervention or lacks mathematical rigor.

Purpose of the Study:

  • To develop a computational method for generating novel variations of existing motion sequences.
  • To ensure these variations maintain aesthetic and mathematical coherence with the original sequence.

Main Methods:

  • A chaotic symbol-sequence reordering technique is employed.
  • Symbolic dynamics are established by mapping motion sequence symbols to a chaotic trajectory.
  • Variations are generated using slightly altered initial conditions and corpus-based graph-theoretic interpolation for smoothing.

Related Experiment Videos

Main Results:

  • The method successfully generates distinct variations of predefined motion sequences.
  • Sensitive dependence on initial conditions ensures the novelty of the generated variations.
  • The attractor structure and symbolic dynamics ensure resemblance between original and varied sequences.

Conclusions:

  • This technique offers a robust method for introducing controlled, yet novel, variations into motion sequences.
  • The approach bridges computational dynamics with artistic and physical movement generation.
  • It provides a framework for exploring variations in choreography, animation, and robotic motion planning.