# Mobile-URSONet: an Embeddable Neural Network for Onboard Spacecraft Pose Estimation

arXiv: https://arxiv.org/abs/2205.02065 · HTML: https://mlsanity.com/paper/2205.02065/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 20 references that are in the map.
- First posted on arXiv 4 May 2022.

## Builds on (most cited first, 10 of 10)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [MobileNetV2: Inverted Residuals and Linear Bottlenecks](https://mlsanity.com/paper/1801.04381/) (2018)
- [MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications](https://mlsanity.com/paper/1704.04861/) (2017)
- [Benchmark Analysis of Representative Deep Neural Network Architectures](https://mlsanity.com/paper/1810.00736/) (2018)
- [Satellite Pose Estimation Challenge: Dataset, Competition Design and Results](https://mlsanity.com/paper/1911.02050/) (2019)
- [Satellite Pose Estimation with Deep Landmark Regression and Nonlinear Pose Refinement](https://mlsanity.com/paper/1908.11542/) (2019)
- [Deep Learning for Spacecraft Pose Estimation from Photorealistic Rendering](https://mlsanity.com/paper/1907.04298/) (2019)
- [Pose Estimation for Non-Cooperative Spacecraft Rendezvous Using Convolutional Neural Networks](https://mlsanity.com/paper/1809.07238/) (2018)
- [Pose Estimation for Non-Cooperative Rendezvous Using Neural Networks](https://mlsanity.com/paper/1906.09868/) (2019)
- [Real-Time, Flight-Ready, Non-Cooperative Spacecraft Pose Estimation Using Monocular Imagery](https://mlsanity.com/paper/2101.09553/) (2021)

## Built on by (most cited first, 5 of 5)

- [A Survey on Deep Learning-Based Monocular Spacecraft Pose Estimation: Current State, Limitations and Prospects](https://mlsanity.com/paper/2305.07348/) (2023)
- [Domain Generalization for In-Orbit 6D Pose Estimation](https://mlsanity.com/paper/2406.11743/) (2024)
- [Real-Time Spacecraft Pose Estimation Using Mixed-Precision Quantized Neural Network on COTS Reconfigurable MPSoC](https://mlsanity.com/paper/2407.06170/) (2024)
- [NeRF-based Visualization of 3D Cues Supporting Data-Driven Spacecraft Pose Estimation](https://mlsanity.com/paper/2509.14890/) (2025)
- [GKNet: Graph-based Keypoints Network for Monocular Pose Estimation of Non-cooperative Spacecraft](https://mlsanity.com/paper/2507.11077/) (2025)

## Abstract (arXiv)

Spacecraft pose estimation is an essential computer vision application that can improve the autonomy of in-orbit operations. An ESA/Stanford competition brought out solutions that seem hardly compatible with the constraints imposed on spacecraft onboard computers. URSONet is among the best in the competition for its generalization capabilities but at the cost of a tremendous number of parameters and high computational complexity. In this paper, we propose Mobile-URSONet: a spacecraft pose estimation convolutional neural network with 178 times fewer parameters while degrading accuracy by no more than four times compared to URSONet.