Abstract
Evolution and learning have historically been interrelated topics, and their interplay is attracting increased interest lately. The emerging new factor in this trend is morphological evolution, the evolution of physical forms within embodied AI systems such as robots. In this study, we investigate a system of hexacopter-type drones with evolvable morphologies and learnable controllers and make contributions to two fields. For aerial robotics, we demonstrate that the combination of evolution and learning can deliver non-conventional drones that significantly outperform the traditional hexacopter on several tasks that are more complex than previously considered in the literature. For the field of Evolutionary Computing, we introduce novel metrics and perform new analyses into the interaction of morphological evolution and learning, uncovering hitherto unidentified effects. Our analysis tools are domain-agnostic, making a methodological contribution towards building solid foundations for embodied AI systems that integrate evolution and learning.
Abstract (translated)
进化和学习在历史上一直是相互关联的主题，最近人们对它们的交互越来越感兴趣。这一趋势中的新兴因素是形态进化，即身体化人工智能系统（如机器人）内部物理形式的演变。在这项研究中，我们调查了一种具有可进化的形态和可学习控制器的六旋翼无人机系统，并对两个领域做出了贡献。 对于空中机器人技术，我们展示了进化与学习相结合能够产生非传统的无人机，在一些比以往文献中更复杂的任务上表现出显著优于传统六旋翼机的效果。而对于进化计算领域，我们引入了新的度量标准，并进行了一系列新分析，探讨形态进化和学习之间的相互作用，揭示了一些前所未有的影响。 我们的分析工具是领域无关的，为构建融合进化与学习的具身AI系统奠定了方法论基础，作出了贡献。
URL
https://arxiv.org/abs/2505.14129
