In the first part, this article presents an overview of Guidance, Navigation and Control (GNC) methodologies developed for space manipulators to perform in-orbit robotic missions, including but not limited to, on-orbit servicing, satellite/station assembly, probing extra-terrestrial objects and space debris mitigation. Some space mission concepts are briefly mentioned, for which space robotics is discussed to be among the most practical and universal solutions. Common phases of an in-orbit robotic mission are identified as: close-range rendezvous, attitude synchronization, target identification, manipulator deployment, capture, and if needed, post-capture maneuvers. Prominent GNC methodologies that are either proposed for or applicable to each phase are extensively reviewed. In the current article, the emphasis is placed on the study of GNC methodologies utilized in attitude synchronization, manipulator deployment, and capture phases, specially the ones reported for use in the two free-floating and free-flying operating regimes of space manipulators. Kinematics and dynamics of space manipulator systems are formulated to help unifying the presentation of the main ideas behind different GNC methodologies. Using a unified notation, comparison tables and discussions provided in this paper, researchers can compare various GNC approaches and contribute to the next-generation GNC systems for space robots. In addition, this survey aids technology users to learn about in-orbit robotic missions and choose appropriate GNC technologies for specific applications. In the second part of this paper, two families of emerging control schemes based upon reinforcement learning and geometric mechanics are introduced as promising research directions in the GNC of space robotic systems. The benefits of implementing these techniques to the GNC of in-orbit robotic missions are discussed. An exclusive study of environmental disturbances affecting space manipulators and their threat to long-term autonomy concludes this article.

在第一部分中，本文概述了为空间操纵器执行在轨机器人任务而开发的制导，导航和控制（GNC）方法论，包括但不限于在轨维修，卫星/站组装，探测额外空间地面物体和空间碎片的缓解。简要提到了一些太空任务概念，其中讨论的太空机器人技术是最实用，通用的解决方案之一。在轨机器人飞行任务的常见阶段被标识为：近距离会合，姿态同步，目标识别，操纵器部署，捕获以及必要时的捕获后操纵。针对每个阶段提出或适用于每个阶段的著名的GNC方法进行了广泛的审查。在当前文章中，重点放在对用于姿态同步，操纵器部署和捕获阶段的GNC方法学的研究上，特别是报告用于空间操纵器的两种自由浮动和自由飞行操作状态的方法。制定了空间操纵器系统的运动学和动力学，以帮助统一表示不同GNC方法论背后的主要思想。使用本文提供的统一符号，比较表和讨论，研究人员可以比较各种GNC方法，并为下一代空间机器人GNC系统做出贡献。此外，这项调查还可以帮助技术用户了解在轨机器人的任务，并为特定应用选择合适的GNC技术。在本文的第二部分，介绍了基于强化学习和几何力学的两个新兴控制方案系列，作为空间机器人系统GNC中有希望的研究方向。讨论了将这些技术应用于在轨机器人任务的GNC的好处。本文对影响空间操纵器的环境扰动及其对长期自治的威胁进行了独家研究。