{
  "id": 2175,
  "url": "https://www.frontiersin.org/articles/10.3389/frobt.2026.1819714",
  "title": "Zero-shot semantic landmark-based visual odometry using foundation models for unstructured planetary exploration",
  "summary": "Precise autonomous navigation on unstructured planetary surfaces is a critical prerequisite for future exploration missions, particularly in GNSS-denied environments such as the Lunar South Pole or Martian deserts. Traditional Visual Odometry (VO) methods, which rely on tracking low-level geometric features (e.g., corners), often fail under the extreme illumination contrast of the Moon or the textural monotony of the Martian regolith. In this work, we present a zero-shot semantic landmark-based ",
  "authors": "Cristina Pérez-Ramos",
  "category": "research",
  "topics": "privacy-surveillance,environment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-08T00:00:00.000Z",
  "fetched_at": "2026-07-14T16:11:46.979Z",
  "source_slug": "x-frontiers-in-robotics-and-ai",
  "source_name": "Frontiers in Robotics and AI",
  "source_homepage": "https://www.frontiersin.org/journals/robotics-and-ai",
  "ethics_ai_record_url": "https://ethics.ai/record/2175",
  "original_url": "https://www.frontiersin.org/articles/10.3389/frobt.2026.1819714",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}