The rapid developments of Artificial Intelligence in the last decade are influencing Aerospace Engineering to a great extent and research in this context is proliferating. We share our observations on the recent developments in the area of Spacecraft Guidance Dynamics and Control, giving selected examples on success stories that have been motivated by mission designs. Our focus is on evolutionary optimisation, tree searches and machine learning, including deep learning and reinforcement learning as the key technologies and drivers for current and future research in the field. From a high-level perspective, we survey various scenarios for which these approaches have been successfully applied or are under strong scientific investigation. Whenever possible, we highlight the relations and synergies that can be obtained by combining different techniques and projects towards future domains for which newly emerging artificial intelligence techniques are expected to become game changers.
翻译:过去十年中人造情报的迅速发展在很大程度上正在影响航空航天工程,这方面的研究正在扩散。我们分享我们关于航天器指导动态和控制领域最近发展的意见,举出由飞行任务设计所激发的成功事例的选定例子。我们的重点是进化优化、树木搜索和机器学习,包括深造和强化学习,作为目前和今后该领域研究的关键技术和驱动因素。我们从高级别的角度,对成功应用这些方法或正在大力进行科学调查的各种设想方案进行了调查。我们尽可能强调通过将不同技术和项目结合到未来领域可以实现的关系和协同作用。在这些领域,新的人工智能技术有望成为这些领域的游戏变革者。