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This study investigates a system of hexacopter type drones with evolvable morphologies and learnable controllers. The combination of morphological evolution and reinforcement learning is shown to produce unconventional drones that significantly outperform the traditional hexacopter on several tasks that are more complex than previously considered in the literature. In addition, novel metrics are introduced and new analyses are conducted on the interaction between morphological evolution and learning, uncovering previously unidentified effects.

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Unconventional Hexacopters via Evolution and Learning: Performance Gains and New Insights

  • 会议论文

  • 发表日期：

    2026年

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  • Jed R. Muff,
  • Keiichi Ito,
  • Elijah H. W. Ang,
  • Karine Miras,
  • A. E. Eiben

摘要

This study investigates a system of hexacopter type drones with evolvable morphologies and learnable controllers. The combination of morphological evolution and reinforcement learning is shown to produce unconventional drones that significantly outperform the traditional hexacopter on several tasks that are more complex than previously considered in the literature. In addition, novel metrics are introduced and new analyses are conducted on the interaction between morphological evolution and learning, uncovering previously unidentified effects.