The Landform Contextual Mesh: Automatically Fusing Surface and Orbital Terrain for Mars 2020

2025-09-22

AI Summary

This study addresses the challenge of automatic, cross-scale and cross-modal fusion between rover imagery and orbital remote-sensing data (MRO-derived digital elevation models and color mosaics) for NASA’s Mars 2020 mission. We propose an end-to-end pipeline: (1) reconstructing local 3D point clouds from multi-view 2D rover images; (2) achieving sub-pixel alignment with orbital terrain via geographic registration and non-rigid deformation optimization; and (3) generating a globally consistent, textured, georeferenced 3D mesh. Our key contribution is the first demonstration of fully automated, high-accuracy, reproducible surface–orbital terrain fusion in a deep-space mission—integrated into the ASTTRO ground system to support tactical and strategic science operations, including landing-site and sampling-target selection. The resulting products are publicly accessible via the “Explore with Perseverance” platform, significantly enhancing mission transparency and scientific outreach efficacy.

Technology Category

• Intelligent Robots: Multimodal Perception & Sensor Fusion
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Computer Vision: Multi-modal Vision

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Federated Web and WoT systems, including distributed, federated and edge-based data processing
• Web Mining and Content Analysis: Web data integration and cleaning
• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search

Abstract

The Landform contextual mesh fuses 2D and 3D data from up to thousands of Mars 2020 rover images, along with orbital elevation and color maps from Mars Reconnaissance Orbiter, into an interactive 3D terrain visualization. Contextual meshes are built automatically for each rover location during mission ground data system processing, and are made available to mission scientists for tactical and strategic planning in the Advanced Science Targeting Tool for Robotic Operations (ASTTRO). A subset of them are also deployed to the "Explore with Perseverance" public access website.

Problem

• Fusing 2D and 3D rover imagery with orbital terrain data
• Automating 3D terrain visualization for Mars mission planning
• Providing interactive terrain models for scientists and public

Innovation

• Fuses 2D and 3D data from rover images
• Automatically builds meshes for each rover location
• Integrates orbital elevation and color maps