Control of Networked Systems Group, Department of Smart Systems Technologies, University of Klagenfurt, Klagenfurt, Austria.
Astrobiology. 2020 Nov;20(11):1321-1337. doi: 10.1089/ast.2019.2036.
As a part of the AMADEE-18 analog Mars mission, designed to study challenges associated with human-based exploration of the Red Planet, we focused our team efforts on testing means to localize an unmanned aerial vehicle (UAV) on Mars. Robot helicopters, such as the one selected for a technology demonstration as a part of NASA's Mars 2020 mission, are small and their performance is computationally limited. An essential aspect of navigation and path planning of an autonomous helicopter is accurate localization of the robot. In the absence of a global positioning system, a computationally efficient localization technology that can be applied on Mars is visual-inertial odometry (VIO). The AMADEE-18 mission provided an opportunity to test the feasibility of a state-of-the-art VIO algorithm and the camera in a Mars-like analog environment. The flight datasets included different terrain structures that challenged the functionality of VIO algorithms. The experiment has yielded valuable insights into the desired surface structure, texture, and mission times for surface relative navigation of UAV on Mars.
作为 AMMADEE-18 模拟火星任务的一部分，该任务旨在研究与人类探索红色星球相关的挑战，我们的团队专注于测试在火星上定位无人驾驶飞行器 (UAV) 的方法。机器人直升机，例如作为 NASA 火星 2020 任务技术演示的一部分而选择的直升机，体积小，其性能在计算上受到限制。自主直升机的导航和路径规划的一个重要方面是机器人的精确定位。在没有全球定位系统的情况下，可以在火星上应用的计算效率高的定位技术是视觉惯性里程计 (VIO)。AMMADEE-18 任务提供了一个机会，可以在类似于火星的模拟环境中测试最先进的 VIO 算法和相机的可行性。飞行数据集包括不同的地形结构，这些结构挑战了 VIO 算法的功能。该实验深入了解了在火星上进行 UAV 相对表面导航所需的表面结构、纹理和任务时间。
