Descent Trajectory Recovery of Chang’e-4 Lander Based on Descent Images

Wan, Wenhui; Liu, Zaihua; Liu, B.; Di, Kaichang; Wang, J.; Liu, C.; Yu, Tianyi; Miao, Yongwu; Peng, Man; Wang, Yilong; Gou, Sheng

doi:10.5194/isprs-archives-xlii-2-w13-1457-2019

Cited by 5 publications

(7 citation statements)

References 3 publications

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“…High-precision lander localization in multi-source data is valuable to support the synergistic scientific investigation of the landing site using multiple data sets. In addition to lander localization, the descent and landing trajectory can be recovered based on bundle adjustment of sequential descent images (Liu, Xu, and Liu 2014;Wan, Liu, and Liu 2019;.…”

Section: Lander Localizationmentioning

confidence: 99%

Geospatial technologies for Chang’e-3 and Chang’e-4 lunar rover missions

Liu

Wan

et al. 2020

Geo-spatial Information Science

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This paper presents a brief overview of the geospatial technologies developed and applied in Chang'e-3 and Chang'e-4 lunar rover missions. Photogrammetric mapping techniques were used to produce topographic products of the landing site with meter level resolution using orbital images before landing, and to produce centimeter-resolution topographic products in near real-time after landing. Visual positioning techniques were used to determine the locations of the two landers using descent images and orbital basemaps immediately after landing. During surface operations, visual-positioning-based rover localization was performed routinely at each waypoint using Navcam images. The topographic analysis and rover localization results directly supported waypoint-to-waypoint path planning, science target selection and scientific investigations. A GIS-based digital cartography system was also developed to support rover teleoperation.

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Section: Lander Localizationmentioning

confidence: 99%

Geospatial technologies for Chang’e-3 and Chang’e-4 lunar rover missions

Liu

Wan

et al. 2020

Geo-spatial Information Science

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“…Because the CE-4 landing zone is on the lunar farside, conventional radio measurement methods, such as ranging, doppler and VLBI, cannot be used during the powered descent stage of the detector (Liu et al, 2019;Wan et al, 2019). Therefore, vision-based positioning technology has become the preferred tool.…”

Section: High Precision Localization Of the Landing Point Based On Multi-source Imagesmentioning

confidence: 99%

“…This was the first successful application of a vision-based landing site positioning method based on computer vision in Chinese lunar program (Wang et al, 2019;Di et al, 2019a). After landing, a 0.03 m/pixel DOM, which covers an area of 211 m × 187 m, was generated using the descent images, and it is used as one of the base maps for the overall rover path planning (Wan et al, 2019).…”

Section: Lander Localization and Analysis Of The Terrain Of The Landing Areamentioning

confidence: 99%

Computer Vision in the Teleoperation of the Yutu-2 Rover

Wang

et al. 2020

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. On January 3, 2019, the Chang'e-4 (CE-4) probe successfully landed in the Von Kármán crater inside the South Pole-Aitken (SPA) basin. With the support of a relay communication satellite "Queqiao" launched in 2018 and located at the Earth-Moon L2 liberation point, the lander and the Yutu-2 rover carried out in-situ exploration and patrol surveys, respectively, and were able to make a series of important scientific discoveries. Owing to the complexity and unpredictability of the lunar surface, teleoperation has become the most important control method for the operation of the rover. Computer vision is an important technology to support the teleoperation of the rover. During the powered descent stage and lunar surface exploration, teleoperation based on computer vision can effectively overcome many technical challenges, such as fast positioning of the landing point, high-resolution seamless mapping of the landing site, localization of the rover in the complex environment on the lunar surface, terrain reconstruction, and path planning. All these processes helped achieve the first soft landing, roving, and in-situ exploration on the lunar farside. This paper presents a high-precision positioning technology and positioning results of the landing point based on multi-source data, including orbital images and CE-4 descent images. The method and its results have been successfully applied in an actual engineering mission for the first time in China, providing important support for the topographical analysis of the landing site and mission planning for subsequent teleoperations. After landing, a 0.03 m resolution DOM was generated using the descent images and was used as one of the base maps for the overall rover path planning. Before each movement, the Yutu-2 rover controlled its hazard avoidance cameras (Hazcam), navigation cameras (Navcam), and panoramic cameras (Pancam) to capture stereo images of the lunar surface at different angles. Local digital elevation models (DEMs) with a 0.02 m resolution were routinely produced at each waypoint using the Navcam and Hazcam images. These DEMs were then used to design an obstacle recognition method and establish a model for calculating the slope, aspect, roughness, and visibility. Finally, in combination with the Yutu-2 rover mobility characteristics, a comprehensive cost map for path search was generated.By the end of the first 12 lunar days, the Yutu-2 rover has been working on the lunar farside for more than 300 days, greatly exceeding the projected service life. The rover was able to overcome the complex terrain on the lunar farside, and travelled a total distance of more than 300 m, achieving the "double three hundred" breakthrough. In future manned lunar landing and exploration of Mars by China, computer vision will play an integral role to support science target selection and scientific investigations, and will become an extremely important core technology for various engineering tasks.

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“…Xu et al proposed an optimization algorithm to improve the surface normal vector by combining the reflectivity model [26]. For the Chang'e-4 mission, Liu et al made use of the collinear equation combined with least squares to recover the lander trajectory [27], while Di et al mapped the landing area [28][29][30][31].…”

Section: Introductionmentioning

confidence: 99%

Trajectory Recovery and Terrain Reconstruction Based on Descent Images under Dual-Restrained Conditions: Tianwen-1

Chen

Liu

et al. 2022

Remote Sensing

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Tianwen-1 is the first Mars probe launched by China and the first mission in the world to successfully complete the three steps of exploration (orbiting, landing, and roving) at the one time. Based on the unverifiable descent images which cover the full range of the landing area, trajectory recovery and fine terrain reconstruction are important parts of the planetary exploration process. In this paper, a novel trajectory recovery and terrain reconstruction (TR-TR) algorithm employing descent images is proposed for the dual-restrained conditions: restraints of the flat terrain resulting in an unstable solution of the descent trajectory and of the parabolic descent trajectory causing low accuracy of terrain reconstruction, respectively. A landing simulation experiment on a landing field with Mars-like landform was carried out to test the robustness and feasibility of the algorithm. The experiment result showed that the horizontal error of the recovered trajectory didn’t exceed 0.397 m, and the elevation error of the reconstructed terrain was no more than 0.462 m. The algorithm successfully recovered the descent trajectory and generated high-resolution terrain products using in-orbit data of Tianwen-1, which provided effective support for the mission planning of the Zhurong rover. The analysis of the results indicated that the descent trajectory has parabolic properties. In addition, the reconstructed terrain contains abundant information and the vertical root mean square error (RMSE) of ground control points is smaller than 1.612 m. Terrain accuracy obtained by in-orbit data is lower than that obtained by field experiment. The work in this paper has made important contributions to the surveying and mapping of Tianwen-1 and has great application value.

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Descent Trajectory Recovery of Chang’e-4 Lander Based on Descent Images

Cited by 5 publications

References 3 publications

Geospatial technologies for Chang’e-3 and Chang’e-4 lunar rover missions

Geospatial technologies for Chang’e-3 and Chang’e-4 lunar rover missions

Computer Vision in the Teleoperation of the Yutu-2 Rover

Trajectory Recovery and Terrain Reconstruction Based on Descent Images under Dual-Restrained Conditions: Tianwen-1

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