基于空地影像多层级匹配的火星巡视器定位与地面验证

doi:10.11947/j.AGCS.2023.20210635

测绘学报 ›› 2023, Vol. 52 ›› Issue (4): 579-587.doi: 10.11947/j.AGCS.2023.20210635

基于空地影像多层级匹配的火星巡视器定位与地面验证

曹子龙^1,2, 童小华^1,2,3, 许雄^1,2,3, 叶真^1,2,3, 肖长江^1,2,3

1. 同济大学测绘与地理信息学院, 上海 200092;
2. 上海市航天测绘遥感与空间探测重点实验室, 上海 200092;
3. 同济大学上海自主智能无人系统科学中心, 上海 201210

收稿日期:2021-11-24 修回日期:2022-10-20 发布日期:2023-05-05
通讯作者: 许雄 E-mail:xvxiong@tongji.edu.cn
作者简介:曹子龙(1998-),男,博士生,研究方向为视觉导航定位。E-mail:xiaocao@tongji.edu.cn
基金资助:
国家自然科学基金(42241167;41971299;42221002);上海市级科技重大专项(2021SHZDZX0100);上海市科学技术委员会科研计划(19511132101)

Research and ground-based validation on Mars rover localization based on multi-level images matching

CAO Zilong^1,2, TONG Xiaohua^1,2,3, XU Xiong^1,2,3, YE Zhen^1,2,3, XIAO Changjiang^1,2,3

1. College of Surveying and Geo-informatics, Tongji University, Shanghai 200092, China;
2. Shanghai Key Laboratory for Planetary Mapping and Remote Sensing for Deep Space Exploration, Tongji University, Shanghai 200092, China;
3. Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai 201210, China

Received:2021-11-24 Revised:2022-10-20 Published:2023-05-05
Supported by:
The National Natural Science Foundation of China (Nos. 42241167;41971299;42221002);The Shanghai Municipal Science and Technology Major Project (No. 2021SHZDZX0100);The Shanghai Municipal Commission of Science and Technology Project(No. 19511132101)

摘要/Abstract

摘要： 深空探测巡视任务中巡视器的高精度定位对于巡视器的自身安全与持续运行至关重要。巡视器定位主要包括相对定位和绝对定位两种方式,其中绝对定位方法主要是利用轨道器/着陆器的数据为基准确定巡视器在全局坐标系下的位置。美国Mars 2020任务携带的机智号无人机在火星环境下完成了飞行验证,它能够获得高分辨率的火星表面影像,从而为火星巡视器绝对定位提供了新思路。据此,本文提出了一种卫星-无人机-巡视器影像协同的多分辨率影像匹配绝对定位框架。首先,利用运动恢复结构(structure from motion,SFM)方法对无人机影像进行三维重建,获取局部高分辨率三维地图;然后,开展巡视器影像与无人机影像的多视角匹配,并基于匹配结果利用后方交会实现巡视器在无人机局部地图中的高精度定位;最后,通过局部无人机影像与卫星影像的配准,实现卫星影像全局坐标系下的巡视器绝对定位。为验证本文方法的可行性,开展了巡视器定位仿真试验,试验结果验证了本文方法的可行性,能够为后续我国开展类似工程任务提供参考。

关键词: 深空探测, 火星无人机, 空地影像匹配, 大倾角影像后方交会, 绝对定位

Abstract: The high-precision positioning of the rover in deep space exploration is essential for its safety and the success of the exploration missions. Two types of positioning methods for rovers are commonly used: relative and absolute positioning. The absolute positioning method mainly uses the orbiter/lander images as a reference to determine the rover location in the global coordinate system. Considering that an unmanned aerial vehicle (UAV) was carried in the Mars 2020 Project for the first time and finally verified in the Mars environment, high-resolution images from the UAV can therefore be used for rover localization. In this paper, a novel localization framework for Mars rover was proposed by matching multi-source images from orbiter, UAV and the rover respectively. Firstly, the structure from motion method was introduced to reconstruct the regional 3D high-resolution terrain from UAV images. Furthermore, a multi-view matching strategy was designed for UAV and rover images to determine the rover position in the reconstructed local 3D map by the space resection method. Finally, the rover position in the global coordinate system can be obtained by matching the UAV with the orbiter images. To verify the effectiveness of the proposed method, a simulated experiment was designed based on the test field for deep space exploration in Tongji university. The experimental result shows that the proposed localization method can generate high accuracy positions for Mars exploration with the assistance of high-resolution UAV images, and therefore support the following similar exploration missions for rovers.

Key words: deep space exploration, Mars UAV, aerial-ground image matching, space resection with large angle, rover global localization

中图分类号:

P237

曹子龙, 童小华, 许雄, 叶真, 肖长江. 基于空地影像多层级匹配的火星巡视器定位与地面验证[J]. 测绘学报, 2023, 52(4): 579-587.

CAO Zilong, TONG Xiaohua, XU Xiong, YE Zhen, XIAO Changjiang. Research and ground-based validation on Mars rover localization based on multi-level images matching[J]. Acta Geodaetica et Cartographica Sinica, 2023, 52(4): 579-587.

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基于空地影像多层级匹配的火星巡视器定位与地面验证

Research and ground-based validation on Mars rover localization based on multi-level images matching

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