# NaRPA: Navigation and Rendering Pipeline for Astronautics

arXiv: https://arxiv.org/abs/2211.01566 · HTML: https://mlsanity.com/paper/2211.01566/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 123 references that are in the map.
- First posted on arXiv 3 Nov 2022.

## Builds on (most cited first, 4 of 4)

- [A Survey on Deep Learning Techniques for Stereo-based Depth Estimation](https://mlsanity.com/paper/2006.02535/) (2020)
- [Scientific image rendering for space scenes with the SurRender software](https://mlsanity.com/paper/1810.01423/) (2018)
- [Image simulation for space applications with the SurRender software](https://mlsanity.com/paper/2106.11322/) (2021)
- [FPGA Hardware Acceleration for Feature-Based Relative Navigation Applications](https://mlsanity.com/paper/2210.09481/) (2022)

## Built on by (most cited first, 2 of 2)

- [Icy Moon Surface Simulation and Stereo Depth Estimation for Sampling Autonomy](https://mlsanity.com/paper/2401.12414/) (2024)
- [Differentiable Rendering for Pose Estimation in Proximity Operations](https://mlsanity.com/paper/2212.12668/) (2022)

## Abstract (arXiv)

This paper presents the applications of scientific ray-tracing in modeling and simulating light transport for space-borne image data generation. A ray-tracing engine, the Navigation and Rendering Pipeline for Astronautics (NaRPA), is introduced as a rendering framework to generate virtual datasets and support simulations for robust navigation pipelines. Sensor and environment models that enable the synthesis of space-to-space and ground-to-space virtual observations are presented. The work demonstrates the capabilities of simulating passive and active vision-based sensors using NaRPA to facilitate the design, testing, and verification of aerospace visual navigation algorithms. Additionally, the paper describes a velocimeter LiDAR model and its statistical validation with experimental data.