Cooperative Relative Navigation for Space Rendezvous and Proximity Operations using Controlled Active Vision

摘要

This work aims to solve the problem of relative navigation for space rendezvous and proximity operations using a monocular camera in a numerically efficient manner. It is assumed that the target spacecraft has a special pattern to aid the task of relative pose estimation, and that the chaser spacecraft uses a monocular camera as the primary visual sensor. In this sense, the problem falls under the category of cooperative relative navigation in orbit. While existing systems for cooperative localization with fiducial markers allow full six-degrees-of-freedom pose estimation, the majority of them are not suitable for in-space cooperative navigation (especially when involving a small-size chaser spacecraft), due to their computational cost. Moreover, most existing fiducial-based localization methods are designed for ground-based applications with limited range (e.g., ground robotics, augmented reality), and their performance deteriorates under large-scale changes, such as those encountered in space applications. Using an adaptive visual algorithm, we propose an accurate and numerically efficient approach for real-time vision-based relative navigation, especially designed for space robotics applications. The proposed method achieves low computational cost and high accuracy and robustness via the following innovations: first, an adaptive visual pattern detection scheme based on the estimated relative pose is proposed, which improves both the efficiency of detection and the accuracy of pose estimates; second, a parametric blob detector called Box-LoG is used, which is computationally efficient; and third, a fast and robust algorithm is introduced, which jointly solves the data association and pose estimation problems. In addition to having an accuracy comparable to state-of-the-art cooperative localization algorithms, our method demonstrates a significant improvement in speed and robustness for scenarios with large range changes. A vision-based closed-loop experiment using the Autonomous Spacecraft Testing of Robotic Operations in Space (ASTROS) testbed demonstrates the performance benefits of the proposed approach.