This paper presents a vision guidance and control method for autonomous robotic capture and stabilization of orbital objects in a time-critical manner. The method takes into account various operational and physical constraints, including ensuring a smooth capture, handling line-of-sight (LOS) obstructions of the target, and staying within the acceleration, force, and torque limits of the robot. Our approach involves the development of an optimal control framework for an eye-to-hand visual servoing method, which integrates two sequential sub-maneuvers: a pre-capturing maneuver and a post-capturing maneuver, aimed at achieving the shortest possible capture time. Integrating both control strategies enables a seamless transition between them, allowing for real-time switching to the appropriate control system. Moreover, both controllers are adaptively tuned through vision feedback to account for the unknown dynamics of the target. The integrated estimation and control architecture also facilitates fault detection and recovery of the visual feedback in situations where the feedback is temporarily obstructed. The experimental results demonstrate the successful execution of pre- and post-capturing operations on a tumbling and drifting target, despite multiple operational constraints.

翻译：本文提出了一种视觉引导与控制方法，用于在时间紧迫条件下自主捕获并稳定轨道目标。该方法考虑了多种操作与物理约束，包括确保捕获过程平滑、处理目标视线遮挡，以及将机器人的加速度、力和力矩控制在限制范围内。我们的方法开发了一种最优控制框架，用于眼手视觉伺服技术，该框架整合了两个连续子机动：捕获前机动与捕获后机动，旨在实现最短的捕获时间。通过整合两种控制策略，可实现两者之间的无缝切换，从而允许实时切换到合适的控制系统。此外，两个控制器均通过视觉反馈进行自适应调整，以应对目标未知的动力学特性。集成的估计与控制架构还能在视觉反馈暂时受阻时进行故障检测与恢复。实验结果表明，尽管存在多重操作约束，该方法仍能成功完成对翻滚与漂移目标的捕获前与捕获后操作。