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

arXiv: https://arxiv.org/abs/2408.01035 · HTML: https://mlsanity.com/paper/2408.01035/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 6 of its 20 references that are in the map.
- First posted on arXiv 2 Aug 2024.

## Builds on (most cited first, 6 of 6)

- [Open3D: A Modern Library for 3D Data Processing](https://mlsanity.com/paper/1801.09847/) (2018)
- [U2-Net: Going Deeper with Nested U-Structure for Salient Object Detection](https://mlsanity.com/paper/2005.09007/) (2020)
- [Pose Estimation for Non-Cooperative Spacecraft Rendezvous Using Convolutional Neural Networks](https://mlsanity.com/paper/1809.07238/) (2018)
- [PyMatting: A Python Library for Alpha Matting](https://mlsanity.com/paper/2003.12382/) (2020)
- [Lower Gravity Demonstratable Testbed for Space Robot Experiments](https://mlsanity.com/paper/2309.10268/) (2023)
- [Space Debris Reliable Capturing by a Dual-Arm Orbital Robot: Detumbling and Caging](https://mlsanity.com/paper/2405.00943/) (2024)

## Abstract (arXiv)

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.