Environmental Adaptation of Robot Morphology and Control Through Real-World Evolution
Environmental Adaptation of Robot Morphology and Control Through Real-World Evolution
复制标题
通过现实世界进化实现机器人形态和控制的环境适应
DOI：
10.1162/evco_a_00291
复制
发表时间：
2020
影响因子：
6.8
通讯作者：
K. Glette
中科院分区：
文献类型：
--
作者：
T. Nygaard;Charles Patrick Martin;David Howard;J. Tørresen;K. Glette
摘要在真实的世界中运行的机器人将经历一系列不同的环境和任务。机器人必须具有适应环境的能力，才能在变化的环境中有效地工作。进化机器人旨在通过优化机器人的控制和身体（形态）来解决这个问题，允许适应内部和外部因素。这一领域的大部分工作都是在物理模拟器中完成的，这些模拟器相对简单，无法复制真实的世界中发现的丰富的相互作用。解决方案，依赖于控制，身体和环境之间的复杂的相互作用，因此很少found.In这篇文章中，我们完全依赖于现实世界的评估和应用进化搜索产生的形态和控制的组合，我们的机械自我重构四足机器人。我们在两个不同的物理表面上发展解决方案，并在控制和形态方面分析结果。然后，我们过渡到两个以前看不见的表面，以证明我们的方法的一般性。我们发现，进化搜索发现高性能和多样化的形态控制器配置，通过适应控制和身体的物理环境的不同属性。我们还发现，形态和控制不同的环境之间的统计意义。此外，我们观察到，我们的方法允许形态和控制参数转移到以前看不见的地形，证明了我们的方法的一般性。
Abstract Robots operating in the real world will experience a range of different environments and tasks. It is essential for the robot to have the ability to adapt to its surroundings to work efficiently in changing conditions. Evolutionary robotics aims to solve this by optimizing both the control and body (morphology) of a robot, allowing adaptation to internal, as well as external factors. Most work in this field has been done in physics simulators, which are relatively simple and not able to replicate the richness of interactions found in the real world. Solutions that rely on the complex interplay among control, body, and environment are therefore rarely found. In this article, we rely solely on real-world evaluations and apply evolutionary search to yield combinations of morphology and control for our mechanically self-reconfiguring quadruped robot. We evolve solutions on two distinct physical surfaces and analyze the results in terms of both control and morphology. We then transition to two previously unseen surfaces to demonstrate the generality of our method. We find that the evolutionary search finds high-performing and diverse morphology-controller configurations by adapting both control and body to the different properties of the physical environments. We additionally find that morphology and control vary with statistical significance between the environments. Moreover, we observe that our method allows for morphology and control parameters to transfer to previously unseen terrains, demonstrating the generality of our approach.
自动变形以恢复受损机器人的功能
DOI：
10.15607/rss.2019
发表时间：
2019
期刊：
Proceedings of Robotics: Science and Systems (2019
影响因子：
--
作者：
Kriegman, Sam;Walker, Stephanie;Shah, Dylan;Levin, Michael;Kramer-Bottiglio, Rebecca;Bongard, Josh
通讯作者：
Bongard, Josh