# A Neuromorphic Vision-Based Measurement for Robust Relative Localization in Future Space Exploration Missions

arXiv: https://arxiv.org/abs/2206.11541 · HTML: https://mlsanity.com/paper/2206.11541/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 53 references that are in the map.
- First posted on arXiv 23 Jun 2022.

## Builds on (most cited first, 8 of 8)

- [Event-based Vision: A Survey](https://mlsanity.com/paper/1904.08405/) (2019)
- [High Speed and High Dynamic Range Video with an Event Camera](https://mlsanity.com/paper/1906.07165/) (2019)
- [Exploring Event Camera-based Odometry for Planetary Robots](https://mlsanity.com/paper/2204.05880/) (2022)
- [Star Tracking using an Event Camera](https://mlsanity.com/paper/1812.02895/) (2018)
- [Spatiotemporal Registration for Event-based Visual Odometry](https://mlsanity.com/paper/2103.05955/) (2021)
- [Neuromorphic Camera Denoising using Graph Neural Network-driven Transformers](https://mlsanity.com/paper/2112.09685/) (2021)
- [A Survey on Hough Transform, Theory, Techniques and Applications](https://mlsanity.com/paper/1502.02160/) (2015)
- [MPPI-VS: Sampling-Based Model Predictive Control Strategy for Constrained Image-Based and Position-Based Visual Servoing](https://mlsanity.com/paper/2104.04925/) (2021)

## Built on by (most cited first, 9 of 9)

- [EV-MGRFlowNet: Motion-Guided Recurrent Network for Unsupervised Event-based Optical Flow with Hybrid Motion-Compensation Loss](https://mlsanity.com/paper/2305.07853/) (2023)
- [E-Calib: A Fast, Robust and Accurate Calibration Toolbox for Event Cameras](https://mlsanity.com/paper/2306.09078/) (2023)
- [Real-time 6-DoF Pose Estimation by an Event-based Camera using Active LED Markers](https://mlsanity.com/paper/2310.16618/) (2023)
- [Neuromorphic Vision-based Motion Segmentation with Graph Transformer Neural Network](https://mlsanity.com/paper/2404.10940/) (2024)
- [A Monocular Event-Camera Motion Capture System](https://mlsanity.com/paper/2502.12113/) (2025)
- [Low-Latency Event-Based Velocimetry for Quadrotor Control in a Narrow Pipe](https://mlsanity.com/paper/2507.15444/) (2025)
- [E-VLC: A Real-World Dataset for Event-based Visible Light Communication And Localization](https://mlsanity.com/paper/2504.18521/) (2025)
- [Event-based Optical Marker Systems: A survey](https://mlsanity.com/paper/2504.20736/) (2025)
- [A Height-Constrained 2-Point Minimal Solver for Pose Estimation from Active LED Markers with Event Cameras](https://mlsanity.com/paper/2608.09520/) (2026)

## Abstract (arXiv)

Space exploration has witnessed revolutionary changes upon landing of the Perseverance Rover on the Martian surface and demonstrating the first flight beyond Earth by the Mars helicopter, Ingenuity. During their mission on Mars, Perseverance Rover and Ingenuity collaboratively explore the Martian surface, where Ingenuity scouts terrain information for rover's safe traversability. Hence, determining the relative poses between both the platforms is of paramount importance for the success of this mission. Driven by this necessity, this work proposes a robust relative localization system based on a fusion of neuromorphic vision-based measurements (NVBMs) and inertial measurements. The emergence of neuromorphic vision triggered a paradigm shift in the computer vision community, due to its unique working principle delineated with asynchronous events triggered by variations of light intensities occurring in the scene. This implies that observations cannot be acquired in static scenes due to illumination invariance. To circumvent this limitation, high frequency active landmarks are inserted in the scene to guarantee consistent event firing. These landmarks are adopted as salient features to facilitate relative localization. A novel event-based landmark identification algorithm using Gaussian Mixture Models (GMM) is developed for matching the landmarks correspondences formulating our NVBMs. The NVBMs are fused with inertial measurements in proposed state estimators, landmark tracking Kalman filter (LTKF) and translation decoupled Kalman filter (TDKF) for landmark tracking and relative localization, respectively. The proposed system was tested in a variety of experiments and has outperformed state-of-the-art approaches in accuracy and range.