A Neuromorphic Vision-Based Measurement for Robust Relative Localization in Future Space Exploration Missions
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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.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 8 of its 53 references that are in the map. First posted on arXiv 23 Jun 2022.
Builds on
8 of 53 references.
References · 8
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- 2022Exploring Event Camera-based Odometry for Planetary Robotscited by 34
- 2018Star Tracking using an Event Cameracited by 30
- 2021Spatiotemporal Registration for Event-based Visual Odometrycited by 21
- 2021Neuromorphic Camera Denoising using Graph Neural Network-driven Transformerscited by 15
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Built on by
Citing papers per year: 2023: 3; 2024: 1; 2025: 4; 2026: 1.
9 papers.
- 2023EV-MGRFlowNet: Motion-Guided Recurrent Network for Unsupervised Event-based Optical Flow with Hybrid Motion-Compensation Losscited by 9
- 2023E-Calib: A Fast, Robust and Accurate Calibration Toolbox for Event Camerascited by 9
- 2023Real-time 6-DoF Pose Estimation by an Event-based Camera using Active LED Markerscited by 8
- 2024Neuromorphic Vision-based Motion Segmentation with Graph Transformer Neural Networkcited by 4
- 2025A Monocular Event-Camera Motion Capture Systemcited by 3
- 2025Low-Latency Event-Based Velocimetry for Quadrotor Control in a Narrow Pipecited by 2
- 2025E-VLC: A Real-World Dataset for Event-based Visible Light Communication And Localizationcited by 1
- 2025Event-based Optical Marker Systems: A surveycited by 1
- 2026A Height-Constrained 2-Point Minimal Solver for Pose Estimation from Active LED Markers with Event Camerascited by 0
- 2026A Height-Constrained 2-Point Minimal Solver for Pose Estimation from Active LED Markers with Event Cameras10 Aug 2026
- 2025Low-Latency Event-Based Velocimetry for Quadrotor Control in a Narrow Pipe21 Jul 2025
- 2025Event-based Optical Marker Systems: A survey29 Apr 2025
- 2025E-VLC: A Real-World Dataset for Event-based Visible Light Communication And Localization25 Apr 2025
- 2025A Monocular Event-Camera Motion Capture System17 Feb 2025
- 2024Neuromorphic Vision-based Motion Segmentation with Graph Transformer Neural Network16 Apr 2024
- 2023Real-time 6-DoF Pose Estimation by an Event-based Camera using Active LED Markers25 Oct 2023
- 2023E-Calib: A Fast, Robust and Accurate Calibration Toolbox for Event Cameras15 Jun 2023
- 2023EV-MGRFlowNet: Motion-Guided Recurrent Network for Unsupervised Event-based Optical Flow with Hybrid Motion-Compensation Loss13 May 2023