Pan-location mapping and localization for the in-situ science exploration of Zhurong Mars rover

Zeng, Xingguo; Li, Jianjun; Ren, Xin; Yan, Wei; Fu, Qiang; Gao, Xinjie; Chen, Wangli; Zuo, Wei; Li, Chunlai

doi:10.1007/s11432-021-3484-2

Cited by 7 publications

(2 citation statements)

References 17 publications

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“…Based on the work [16], [17], we leverage quadrics and cubes to simplify object representation instead of well-trained 3D priors or well-established CAD models. Some lunar landmarks have regular shapes containing big rocks and hills, while others showcase irregular shapes, such as small rocks, dunes, and craters [69]. Depending on the geometric appearances of lunar rocks, we cannot parameterize their orientation since rocks are non-regular.…”

Section: Data Association With Object Instancesmentioning

confidence: 99%

LO-SLAM: Lunar Object-centric SLAM using Point Prompted SAM for Data Association

Tian,

Wan,

Zhang

et al. 2024

Preprint

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To ensure long-term space missions, an autonomous visual navigation system for lunar rovers supporting selfexploration is demanded. While the object-centric localization and mapping problem can be solved through state-of-the-art methods, they greatly rely on human-in-loop remote operations, posing several challenges for the visual system of a rover when operating in a distant, unknown, and feature-sparse lunar environment. This paper presents a SAM-augmented object-centric SLAM framework which enable rovers to estimate the relative distance to the target on lunar surface, thus ensuring the safety of exploration task. Based on the feature-matching baseline and an auto-label segmentation approach, a prompted-based object instance extraction pipeline is first proposed to predict object correspondences at a pixel level. We then integrate with front-end outputs in the middle-end of SLAM to tightly associate reliable object-centric constraints between image frames. Moreover, the data association in LO-SLAM maintains robust camera-object relative position estimation between the camera and target object. Extensive experiments are conducted on our dataset, Stereo Planetary Tracks (SePT). Results show that the proposed LO-SLAM is validated on challenging lunar scenarios with dramatic viewpoints and object scale changes. The average pose errors are less than 0.37 meters in centroid, and the average object-centric trajectory error is less than 0.49%. An open-source dataset has been released at https://github.com/miaTian99/SePT_Stereo-Planetary-Tracks.

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Section: Data Association With Object Instancesmentioning

confidence: 99%

LO-SLAM: Lunar Object-centric SLAM using Point Prompted SAM for Data Association

Tian,

Wan,

Zhang

et al. 2024

Preprint

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“…In both cases, the images and scientific results published so far remain limited. The Chinese Mars mission, Tianwen-1, completed the topographic mapping of the "Lover" landing site, which is not yet open to the public [20,93].…”

Section: Marsmentioning

confidence: 99%

Remote Sensing and Data Analyses on Planetary Topography

2023

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Planetary mapping product established by topographic remote sensing is one of the most significant achievements of contemporary technology. Modern planetary remote sensing technology now measures the topography of familiar solid planets/satellites such as Mars and the Moon with sub-meter precision, and its applications extend to the Kuiper Belt of the Solar System. However, due to a lack of fundamental knowledge of planetary remote sensing technology, the general public and even the scientific community often misunderstand these astounding accomplishments. Because of this technical gap, the information that reaches the public is sometimes misleading and makes it difficult for the scientific community to effectively respond to and address this misinformation. Furthermore, the potential for incorrect interpretation of the scientific analysis might increase as planetary research itself increasingly relies on publicly accessible tools and data without a sufficient understanding of the underlying technology. This review intends to provide the research community and personnel involved in planetary geologic and geomorphic studies with the technical foundation of planetary topographic remote sensing. To achieve this, we reviewed the scientific results established over centuries for the topography of each planet/satellite in the Solar System and concisely presented their technical bases. To bridge the interdisciplinary gap in planetary science research, a special emphasis was placed on providing photogrammetric techniques, a key component of remote sensing of planetary topographic remote sensing.

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Aeolian disruption and reworking of TARs at the Zhurong rover field site, southern Utopia Planitia, Mars

Edgett²,

Wu³

et al. 2022

Earth and Planetary Science Letters

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Pan-location mapping and localization for the in-situ science exploration of Zhurong Mars rover

Cited by 7 publications

References 17 publications

LO-SLAM: Lunar Object-centric SLAM using Point Prompted SAM for Data Association

LO-SLAM: Lunar Object-centric SLAM using Point Prompted SAM for Data Association

Remote Sensing and Data Analyses on Planetary Topography

Aeolian disruption and reworking of TARs at the Zhurong rover field site, southern Utopia Planitia, Mars

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