The Mars Science Helicopter (MSH) mission aims to deploy the next generation of unmanned helicopters on Mars, targeting landing sites in highly irregular terrain such as Valles Marineris, the largest canyons in the Solar system with elevation variances of up to 8000 meters. Unlike its predecessor, the Mars 2020 mission, which relied on a state estimation system assuming planar terrain, MSH requires a novel approach due to the complex topography of the landing site. This work introduces a novel range-visual-inertial odometry system tailored for the unique challenges of the MSH mission. Our system extends the state-of-the-art xVIO framework by fusing consistent range information with visual and inertial measurements, preventing metric scale drift in the absence of visual-inertial excitation (mono camera and constant velocity descent), and enabling landing on any terrain structure, without requiring any planar terrain assumption. Through extensive testing in image-based simulations using actual terrain structure and textures collected in Mars orbit, we demonstrate that our range-VIO approach estimates terrain-relative velocity meeting the stringent mission requirements, and outperforming existing methods.

翻译：火星科学直升机任务旨在将新一代无人直升机部署于火星，其目标着陆点为高度不规则地形，例如太阳系中最大的峡谷——水手号峡谷，其海拔落差高达8000米。与依赖假设平坦地形的状态估计系统的前代任务（火星2020任务）不同，由于着陆点的复杂地形，火星科学直升机任务需要一种全新的方法。本文针对火星科学直升机任务的独特挑战，提出了一种新颖的距离-视觉-惯性里程计系统。我们的系统通过将一致的距离信息与视觉及惯性测量数据相融合，扩展了最先进的xVIO框架，从而在缺乏视觉-惯性激励（单目相机和恒定速度下降）的情况下防止度量尺度漂移，并实现在无需任何平坦地形假设的前提下着陆于任意地形结构。通过在基于图像的仿真中使用火星轨道采集的实际地形结构与纹理进行广泛测试，我们证明，我们的距离-视觉-惯性里程计方法所估计的地形相对速度满足严苛的任务要求，并且性能优于现有方法。