research-article

Evolving CPPNs to grow three-dimensional physical structures

Authors:

Joshua E. Auerbach,

Josh C. BongardAuthors Info & Claims

GECCO '10: Proceedings of the 12th annual conference on Genetic and evolutionary computation

Pages 627 - 634

https://doi.org/10.1145/1830483.1830597

Published: 07 July 2010 Publication History

Abstract

The majority of work in the field of evolutionary robotics concerns itself with evolving control strategies for human designed or bio-mimicked robot morphologies. However, there are reasons why co-evolving morphology along with control may provide a better path towards realizing intelligent agents. Towards this goal, a novel method for evolving three-dimensional physical structures using CPPN-NEAT is introduced which is capable of producing artifacts that capture the non-obvious yet close relationship between function and physical structure. Moreover, it is shown how more fit solutions can be achieved with less computational effort by using growth and environmental CPPN input parameters as well as incremental changes in resolution.

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Cited By

Mertan ACheney N(2024)No-brainer: Morphological Computation Driven Adaptive Behavior in Soft RobotsFrom Animals to Animats 1710.1007/978-3-031-71533-4_6(81-92)Online publication date: 7-Sep-2024
https://doi.org/10.1007/978-3-031-71533-4_6
Eguiarte-Morett LAguilar W(2023)Premature convergence in morphology and control co-evolution: a studyAdaptive Behavior10.1177/10597123231198497Online publication date: 7-Sep-2023
https://doi.org/10.1177/10597123231198497
Iida FGiardina F(2023)On the Timescales of Embodied Intelligence for Autonomous Adaptive SystemsAnnual Review of Control, Robotics, and Autonomous Systems10.1146/annurev-control-063022-0943016:1(95-122)Online publication date: 3-May-2023
https://doi.org/10.1146/annurev-control-063022-094301
Show More Cited By

Index Terms

Evolving CPPNs to grow three-dimensional physical structures
1. Computer systems organization
  1. Embedded and cyber-physical systems
    1. Robotics
2. Computing methodologies
  1. Artificial intelligence
    1. Control methods
      1. Robotic planning
    2. Planning and scheduling
      1. Robotic planning

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Published In

cover image ACM Conferences

GECCO '10: Proceedings of the 12th annual conference on Genetic and evolutionary computation

July 2010

1520 pages

ISBN:9781450300728

DOI:10.1145/1830483

General Chair:
Martin Pelikan
University of Missouri, USA
,
Program Chair:
Jürgen Branke
University of Warwick, Coventry, UK

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation

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Association for Computing Machinery

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Published: 07 July 2010

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GECCO '10: Genetic and Evolutionary Computation Conference

July 7 - 11, 2010

Oregon, Portland, USA

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

Mertan ACheney N(2024)No-brainer: Morphological Computation Driven Adaptive Behavior in Soft RobotsFrom Animals to Animats 1710.1007/978-3-031-71533-4_6(81-92)Online publication date: 7-Sep-2024
https://doi.org/10.1007/978-3-031-71533-4_6
Eguiarte-Morett LAguilar W(2023)Premature convergence in morphology and control co-evolution: a studyAdaptive Behavior10.1177/10597123231198497Online publication date: 7-Sep-2023
https://doi.org/10.1177/10597123231198497
Iida FGiardina F(2023)On the Timescales of Embodied Intelligence for Autonomous Adaptive SystemsAnnual Review of Control, Robotics, and Autonomous Systems10.1146/annurev-control-063022-0943016:1(95-122)Online publication date: 3-May-2023
https://doi.org/10.1146/annurev-control-063022-094301
Scarton LHagg ASilva SPaquete L(2023)On the Suitability of Representations for Quality Diversity Optimization of ShapesProceedings of the Genetic and Evolutionary Computation Conference10.1145/3583131.3590381(963-971)Online publication date: 15-Jul-2023
https://dl.acm.org/doi/10.1145/3583131.3590381
Medvet ENadizar GPigozzi FSalvato E(2023)Evolutionary Machine Learning in RoboticsHandbook of Evolutionary Machine Learning10.1007/978-981-99-3814-8_23(657-694)Online publication date: 2-Nov-2023
https://doi.org/10.1007/978-981-99-3814-8_23
Horibe KWalker KBerg Palm RSudhakaran SRisi S(2022)Severe damage recovery in evolving soft robots through differentiable programmingGenetic Programming and Evolvable Machines10.1007/s10710-022-09433-z23:3(405-426)Online publication date: 12-Jun-2022
https://doi.org/10.1007/s10710-022-09433-z
Lai GLeymarie FLatham WArita TSuzuki R(2021)Virtual Creature Morphology ‐ A ReviewComputer Graphics Forum10.1111/cgf.14266140:2(659-681)Online publication date: 4-Jun-2021
https://doi.org/10.1111/cgf.142661
Collins JCottier BHoward D(2019)Comparing Direct and Indirect Representations for Environment-Specific Robot Component Design2019 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC.2019.8790166(2705-2712)Online publication date: Jun-2019
https://doi.org/10.1109/CEC.2019.8790166
Gu YZhang XWu QLi YZhang BGao FLuo Y(2019)Research on Motion Evolution of Soft Robot Based on VoxCADIntelligent Robotics and Applications10.1007/978-3-030-27535-8_3(26-37)Online publication date: 2-Aug-2019
https://doi.org/10.1007/978-3-030-27535-8_3
Ogawa J(2019)Evolutionary Multi-objective Optimization for Evolving Soft Robots in Different EnvironmentsBio-inspired Information and Communication Technologies10.1007/978-3-030-24202-2_9(112-131)Online publication date: 24-Jul-2019
https://doi.org/10.1007/978-3-030-24202-2_9
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