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Automatic design and manufacture of robotic lifeforms

Author

Listed:
  • Hod Lipson

    (Volen Center for Complex Systems, Brandeis University)

  • Jordan B. Pollack

    (Volen Center for Complex Systems, Brandeis University)

Abstract

Biological life is in control of its own means of reproduction, which generally involves complex, autocatalysing chemical reactions. But this autonomy of design and manufacture has not yet been realized artificially1. Robots are still laboriously designed and constructed by teams of human engineers, usually at considerable expense. Few robots are available because these costs must be absorbed through mass production, which is justified only for toys, weapons and industrial systems such as automatic teller machines. Here we report the results of a combined computational and experimental approach in which simple electromechanical systems are evolved through simulations from basic building blocks (bars, actuators and artificial neurons); the ‘fittest’ machines (defined by their locomotive ability) are then fabricated robotically using rapid manufacturing technology. We thus achieve autonomy of design and construction using evolution in a ‘limited universe’ physical simulation2,3 coupled to automatic fabrication.

Suggested Citation

  • Hod Lipson & Jordan B. Pollack, 2000. "Automatic design and manufacture of robotic lifeforms," Nature, Nature, vol. 406(6799), pages 974-978, August.
  • Handle: RePEc:nat:nature:v:406:y:2000:i:6799:d:10.1038_35023115
    DOI: 10.1038/35023115
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    Cited by:

    1. Miguel Duarte & Vasco Costa & Jorge Gomes & Tiago Rodrigues & Fernando Silva & Sancho Moura Oliveira & Anders Lyhne Christensen, 2016. "Evolution of Collective Behaviors for a Real Swarm of Aquatic Surface Robots," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-25, March.
    2. Da Zhao & Haobo Luo & Yuxiao Tu & Chongxi Meng & Tin Lun Lam, 2024. "Snail-inspired robotic swarms: a hybrid connector drives collective adaptation in unstructured outdoor environments," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    3. Agrim Gupta & Silvio Savarese & Surya Ganguli & Li Fei-Fei, 2021. "Embodied intelligence via learning and evolution," Nature Communications, Nature, vol. 12(1), pages 1-12, December.

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