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

Three generations of automatically designed robots.

J B Pollack1, H Lipson, G Hornby

  • 1DEMO Laboratory Computer Science Dept., Brandeis University, Waltham, MA 02454, USA. pollack@cs.brandeis.edu

Artificial Life
|November 20, 2001
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

Diagnostic accuracy of the Cepheid MTB host response assay for the detection of pulmonary TB.

IJTLD open·2025
Same author

Exploring the high-resolution mapping of gender-disaggregated development indicators.

Journal of the Royal Society, Interface·2017
Same author

Rapid 3D printing of anatomically accurate and mechanically heterogeneous aortic valve hydrogel scaffolds.

Biofabrication·2012
Same author

X-ray diffraction in inorganic chemistry, metallurgy and mineralogy.

Nature·2010
Same author

Preclinical characterization of WAY-211612: a dual 5-HT uptake inhibitor and 5-HT (1A) receptor antagonist and potential novel antidepressant.

British journal of pharmacology·2009
Same author

A computational environment to simulate complex tendinous topologies.

Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference·2007
Same journal

If Turing Played Piano With an Artificial Partner.

Artificial life·2026
Same journal

Discovering Partial Differential Equations With Neural Cellular Automata.

Artificial life·2026
Same journal

Book Review: Exploring the Boundaries of Life-as-It-Is.

Artificial life·2026
Same journal

System 0/1/2/3: Quad-Process Theory for Multitimescale Embodied Collective Cognitive Systems.

Artificial life·2025
Same journal

To Engineer an Angel, First Validate the Devil: Analyzing the "Could Be" in Artificial Life's "Life as-It-Could-Be".

Artificial life·2025
Same journal

Untapped Potential in Self-Optimization of Hopfield Networks: The Creativity of Unsupervised Learning.

Artificial life·2025
See all related articles

Researchers propose evolving robot morphology and controllers simultaneously for automatic design of specialized robots. This approach overcomes limitations in current robotic applications, enabling custom solutions for specific tasks.

Area of Science:

  • Robotics
  • Evolutionary Computation
  • Artificial Intelligence

Background:

  • Current robot design faces limitations, restricting applications to repetitive tasks.
  • General-purpose robots are complex and difficult to control effectively.
  • Existing robotic systems often lack adaptability for diverse or novel challenges.

Purpose of the Study:

  • To present an alternative approach to robot design by co-evolving morphology and control.
  • To demonstrate the automatic design of specialized robots for specific objectives.
  • To review three generations of research in this evolutionary robotics paradigm.

Main Methods:

  • Simultaneous evolution of robot physical form (morphology) and its control system.
  • Utilizing generative, DNA-like encoding for robot design specifications.

Related Experiment Videos

  • Iterative design and manufacturing of robotic systems through evolutionary algorithms.

    • Main Results:

    • Successfully designed specialized static structures through automatic processes.
    • Developed and manufactured dynamic electromechanical systems via evolutionary design.
    • Created modular robots with designs specified by a generative encoding.

    Conclusions:

    • Co-evolution of morphology and controllers offers a powerful method for automatic robot design.
    • This approach enables the creation of specialized robots tailored for specific, short-term objectives.
    • The research demonstrates a pathway beyond the stasis in current robotic applications.