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MANTLE: A Framework for Adaptive In-Situ Planetary Perception Using a Modular Uplink Principle

arXiv · AI, language, vision and robotics · article · Aug 28, 2026 · UTC

Planetary surface exploration missions rely increasingly on autonomous robotic platforms capable of interpreting complex terrain to ensure safe navigation, enable targeted science, and improve operational efficiency, as demonstrated across past Mars missions from Viking through Perseverance. Among the key perception capabilities, landform classification provides contextual information for landing site selection and scientific analysis, while boulder segmentation supports hazard assessment and path planning. This paper presents MANTLE, a multi-task adaptive network for terrain and landform extr

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