On-orbit close proximity operations involve robotic spacecraft maneuvering and making decisions for a growing number of mission scenarios demanding autonomy, including on-orbit assembly, repair, and astronaut assistance. Of these scenarios, on-orbit assembly is an enabling technology that will allow large space structures to be built in-situ, using smaller building block modules. However, robotic on-orbit assembly involves a number of technical hurdles such as changing system models. For instance, grappled modules moved by a free-flying "assembler" robot can cause significant shifts in system inertial properties, which has cascading impacts on motion planning and control portions of the autonomy stack. Further, on-orbit assembly and other scenarios require collision-avoiding motion planning, particularly when operating in a "construction site" scenario of multiple assembler robots and structures. These complicating factors, relevant to many autonomous microgravity robotics use cases, are tackled in the ReSWARM flight experiments as a set of tests on the International Space Station using NASA's Astrobee robots. RElative Satellite sWarming and Robotic Maneuvering, or ReSWARM, demonstrates multiple key technologies for close proximity operations and on-orbit assembly: (1) global long-horizon planning, accomplished using offline and online sampling-based planner options that consider the system dynamics; (2) on-orbit reconfiguration model learning, using the recently-proposed RATTLE information-aware planning framework; and (3) robust control tools to provide low-level control robustness using current system knowledge. These approaches are detailed individually and in an "on-orbit assembly scenario" of multi-waypoint tracking on-orbit. Additionally, detail is provided discussing the practicalities of hardware implementation and unique aspects of working with Astrobee in microgravity.

翻译：在轨近距离操作涉及自主航天器在越来越多需要自主性的任务场景（包括在轨组装、维修和宇航员辅助）中进行机动和决策。其中，在轨组装是一项使能技术，允许通过使用较小的构建模块在现场建造大型空间结构。然而，机器人自主在轨组装面临诸多技术挑战，例如系统模型的动态变化。具体而言，由自由飞行“组装”机器人移动的抓取模块可能导致系统惯性特性发生显著变化，进而对自主堆栈中的运动规划与控制环节产生连锁影响。此外，在轨组装及其他场景要求进行避免碰撞的运动规划，特别是在多个组装机器人和结构共存的“施工现场”场景中。这些与众多自主微重力机器人应用场景相关的复杂因素，已在美国国家航空航天局（NASA）的Astrobee机器人平台上的ReSWARM飞行实验中作为一组国际空间站测试任务进行了攻关。相对卫星群与机器人机动实验（RElative Satellite sWarming and Robotic Maneuvering，简称ReSWARM）展示了近距离操作和在轨组装的多个关键技术：(1) 全局长时域规划，通过考虑系统动力学的离线与在线采样规划器选项实现；(2) 在轨重构模型学习，利用近期提出的RATTLE信息感知规划框架；(3) 鲁棒控制工具，基于当前系统知识提供底层控制鲁棒性。这些方法被逐一详述，并在“在轨组装场景”（即轨上多航点跟踪）中得到验证。此外，本文还详细讨论了硬件实现的实用性问题以及微重力环境下与Astrobee机器人协作的特殊方面。