2020年7月24日 · The landing system onboard Mars 2020 will use technology developed at the Jet Propulsion Laboratory (JPL) called Terrain Relative Navigation (TRN), which will enable the spacecraft to autonomously avoid hazards (e.g., rock fields, crater rims) that exceed the safety requirements of the landing system.

2022年9月30日 · TRN uses a camera to correlate visible terrain features to onboard maps, calculating relative positions and altitudes during descent within seconds. Furthermore, TRN can autonomously navigate spacecraft away from medium to large hazards within a target landing zone to ensure a safe landing for a successful mission.

2025年1月12日 · In response, this paper introduces two approaches for robust image matching under illumination variation: 1) A new correlation-based algorithm — the Lighting Invariant Matching Algorithm (LIMA), and 2) a novel application of deep learning for learning illumination invariant features.

The Toulouse Road Network dataset describes patches of road maps from the city of Toulouse, represented both as spatial graphs G = (A, X) and as grayscale segmentation images. The TRN dataset contains 111,034 data points (map tiles), of which: 80,357 are in the training set (around 72.4%), 11,679 are in the validation set (around 10.5%), 18,998 ...

2024年8月16日 · This presentation will describe the image processing building blocks for development of a TRN system for planetary landing including: image warping, feature selection and image correlation. It will then describe the Lander Vision System (LVS) that integrates these components into a real-time image-based terrain relative navigation system and ...

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TRN, Feature Tracking, Visual Odometry •In the context of this presentation, TRN means matching a camera image to its location on an onboard map to extract the spacecraft altitude and attitude with respect to that map •The onboard map has been loaded ahead of time and built from orbital imagery data

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