ROCVAug 2, 2024

Structure from Motion-based Motion Estimation and 3D Reconstruction of Unknown Shaped Space Debris

arXiv:2408.01035v16 citationsh-index: 7
Originality Synthesis-oriented
AI Analysis

This addresses the critical need for accurate motion estimation to improve the reliability of debris capture missions in space, targeting space agencies and researchers, but it is incremental as it applies an existing method to a new domain.

The paper tackles the problem of estimating the motion and reconstructing the 3D shape of unknown space debris using only 2D images, proposing a Structure from Motion-based algorithm that outputs both shape and pose trajectory for motion estimation, validated with realistic datasets from microgravity experiments and simulations.

With the boost in the number of spacecraft launches in the current decades, the space debris problem is daily becoming significantly crucial. For sustainable space utilization, the continuous removal of space debris is the most severe problem for humanity. To maximize the reliability of the debris capture mission in orbit, accurate motion estimation of the target is essential. Space debris has lost its attitude and orbit control capabilities, and its shape is unknown due to the break. This paper proposes the Structure from Motion-based algorithm to perform unknown shaped space debris motion estimation with limited resources, where only 2D images are required as input. The method then outputs the reconstructed shape of the unknown object and the relative pose trajectory between the target and the camera simultaneously, which are exploited to estimate the target's motion. The method is quantitatively validated with the realistic image dataset generated by the microgravity experiment in a 2D air-floating testbed and 3D kinematic simulation.

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