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Related Experiment Video

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Physical Scaffolding Accelerates the Evolution of Robot Behavior.

David Buckingham1, Josh Bongard2

  • 1Tufts University.

Artificial Life
|August 9, 2017
PubMed
Summary

This study introduces a simulation-to-reality pipeline for evolutionary robotics, using physically scaffolded agents to improve robot performance in high-fidelity simulations. This approach balances simulation speed with real-world grounding for automated robot generation.

Keywords:
Reality gapevolutionminimal cognitionscaffoldingsimulation

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Evolutionary Computation

Background:

  • Robots are often transferred from simulation to reality, with data flowing back to refine simulations.
  • A generalized simulation-to-reality pipeline is proposed, where agents ascend through increasingly realistic simulators.

Purpose of the Study:

  • To introduce and validate a simulation-to-reality pipeline for evolutionary robotics.
  • To demonstrate that physically scaffolded agents can outperform agents trained solely in high-fidelity simulations.

Main Methods:

  • A two-link pipeline was created: a low-fidelity (lo-fi) simulator and a high-fidelity (hi-fi) simulator.
  • Agents evolved controllers and morphologies in the lo-fi simulator before transferring to the hi-fi simulator.
  • Performance was compared against agents that evolved only in the hi-fi simulator under the same computational budget.

Main Results:

  • Physically scaffolded robots achieved higher performance in the hi-fi simulator than robots evolved solely in the hi-fi simulator.
  • This performance advantage was observed for sufficiently difficult tasks.
  • The pipeline demonstrated a balance between accelerating evolution and grounding results in physical reality.

Conclusions:

  • A simulation-to-reality pipeline offers a promising approach for evolutionary robotics.
  • This method can accelerate the evolution of robot controllers and morphologies.
  • The pipeline facilitates scalable, automated robot generation systems without prespecified morphologies.