论文标题
Astroslam：天体附近的自主单眼导航 - 理论和实验
AstroSLAM: Autonomous Monocular Navigation in the Vicinity of a Celestial Small Body -- Theory and Experiments
论文作者
论文摘要
我们提出了Astroslam，这是一种基于独立的视觉解决方案，用于围绕一个未知目标小天体的自动在线导航。 Astroslam是基于大满贯问题作为逐渐生长的因子图的制定，这是通过使用GTSAM库和ISAM2发动机的促进的。通过将传感器融合与轨道运动先验相结合，我们在基线大满贯溶液上实现了提高的性能。我们通过设计一种新型的相对动力学因子将轨道运动约束结合到了因子图中，该因子将航天器的相对姿势与预测源于小体附近的航天器运动的轨迹的相对姿势。我们使用真实的传统任务图像和轨迹数据表明了Astoslam的出色表现，以及由NASA的行星数据系统提供的，以及在3度自由式航天器模拟器测试床上产生的真实内置图像数据。
We propose AstroSLAM, a standalone vision-based solution for autonomous online navigation around an unknown target small celestial body. AstroSLAM is predicated on the formulation of the SLAM problem as an incrementally growing factor graph, facilitated by the use of the GTSAM library and the iSAM2 engine. By combining sensor fusion with orbital motion priors, we achieve improved performance over a baseline SLAM solution. We incorporate orbital motion constraints into the factor graph by devising a novel relative dynamics factor, which links the relative pose of the spacecraft to the problem of predicting trajectories stemming from the motion of the spacecraft in the vicinity of the small body. We demonstrate the excellent performance of AstroSLAM using both real legacy mission imagery and trajectory data courtesy of NASA's Planetary Data System, as well as real in-lab imagery data generated on a 3 degree-of-freedom spacecraft simulator test-bed.
