论文标题
形态变化在进化机器人技术中的作用：最大化性能和鲁棒性
The Role of Morphological Variation in Evolutionary Robotics: Maximizing Performance and Robustness
论文作者
论文摘要
对于获得可变条件的进化算法，用于获取稳健的解决方案并可以越过现实差距，这是必要的。但是，我们尚无分析和理解影响进化过程的不同形态条件的影响的方法，因此选择合适的变异范围。根据形态条件，我们指机器人的起始状态，以及由于噪声而在操作过程中其传感器读数的变化。在本文中，我们介绍了一种允许我们衡量这些形态变化的影响的方法，并分析了变化幅度，引入它们的方式以及不断发展的剂的性能和稳健性之间的关系。我们的结果表明，（i）进化算法可以忍受具有很高影响的形态变化，（ii）影响代理行为的变化要比影响剂或环境的初始状态的变化要好得多，并且（iii）通过多个评估的准确性不始终有用。此外，我们的结果表明，形态变化允许生成在不同条件和不变条件下效果更好的解决方案。
Exposing an Evolutionary Algorithm that is used to evolve robot controllers to variable conditions is necessary to obtain solutions which are robust and can cross the reality gap. However, we do not yet have methods for analyzing and understanding the impact of the varying morphological conditions which impact the evolutionary process, and therefore for choosing suitable variation ranges. By morphological conditions, we refer to the starting state of the robot, and to variations in its sensor readings during operation due to noise. In this article, we introduce a method that permits us to measure the impact of these morphological variations and we analyze the relation between the amplitude of variations, the modality with which they are introduced, and the performance and robustness of evolving agents. Our results demonstrate that (i) the evolutionary algorithm can tolerate morphological variations which have a very high impact, (ii) variations affecting the actions of the agent are tolerated much better than variations affecting the initial state of the agent or of the environment, and (iii) improving the accuracy of the fitness measure through multiple evaluations is not always useful. Moreover, our results show that morphological variations permit generating solutions which perform better both in varying and non-varying conditions.
