mlsanityData to 7 Oct 2026

Real-Time Spacecraft Pose Estimation Using Mixed-Precision Quantized Neural Network on COTS Reconfigurable MPSoC

arXiv 2407.06170 ↗First posted 6 Jun 2024cs.CV cs.AI cs.ARcited by 2

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Abstract (arXiv)

This article presents a pioneering approach to real-time spacecraft pose estimation, utilizing a mixed-precision quantized neural network implemented on the FPGA components of a commercially available Xilinx MPSoC, renowned for its suitability in space applications. Our co-design methodology includes a novel evaluation technique for assessing the layer-wise neural network sensitivity to quantization, facilitating an optimal balance between accuracy, latency, and FPGA resource utilization. Utilizing the FINN library, we developed a bespoke FPGA dataflow accelerator that integrates on-chip weights and activation functions to minimize latency and energy consumption. Our implementation is 7.7 times faster and 19.5 times more energy-efficient than the best-reported values in the existing spacecraft pose estimation literature. Furthermore, our contribution includes the first real-time, open-source implementation of such algorithms, marking a significant advancement in making efficient spacecraft pose estimation algorithms widely accessible. The source code is available at https://github.com/possoj/FPGA-SpacePose.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 17 of its 29 references that are in the map. First posted on arXiv 6 Jun 2024.

Builds on

17 of 29 references.

References · 17

  1. 2018MobileNetV2: Inverted Residuals and Linear Bottleneckscited by 4,773
  2. 2023ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoderscited by 703
  3. 2018HAQ: Hardware-Aware Automated Quantization with Mixed Precisioncited by 426
  4. 2019HAWQ: Hessian AWare Quantization of Neural Networks with Mixed-Precisioncited by 387
  5. 2019Satellite Pose Estimation Challenge: Dataset, Competition Design and Resultscited by 62
  6. 2019Satellite Pose Estimation with Deep Landmark Regression and Nonlinear Pose Refinementcited by 56
  7. 2018FINN-R: An End-to-End Deep-Learning Framework for Fast Exploration of Quantized Neural Networkscited by 54
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  9. 2022Mixed-Precision Neural Network Quantization via Learned Layer-wise Importancecited by 53
  10. 2021Wide-Depth-Range 6D Object Pose Estimation in Spacecited by 45
  11. 2019Pose Estimation for Non-Cooperative Rendezvous Using Neural Networkscited by 21
  12. 2021Real-Time, Flight-Ready, Non-Cooperative Spacecraft Pose Estimation Using Monocular Imagerycited by 15
5 more
  1. 2022CA-SpaceNet: Counterfactual Analysis for 6D Pose Estimation in Spacecited by 13
  2. 2022Mixed-Precision Neural Networks: A Surveycited by 7
  3. 2022Mobile-URSONet: an Embeddable Neural Network for Onboard Spacecraft Pose Estimationcited by 5
  4. 2022BARVINN: Arbitrary Precision DNN Accelerator Controlled by a RISC-V CPUcited by 5
  5. 2022Deep Learning for Real Time Satellite Pose Estimation on Low Power Edge TPUcited by 4

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Cited by year

Citing papers per year: 2025: 2.

2 papers.

  1. 2025NeRF-based Visualization of 3D Cues Supporting Data-Driven Spacecraft Pose Estimationcited by 2
  2. 2025Event-RGB Fusion for Spacecraft Pose Estimation Under Harsh Lightingcited by 1