Marc Moore
Papers
1
Total Citations
2
H-Index
1
About
Marc Moore is a leading researcher in autonomous navigation, specializing in off-road robotics and uncertainty-aware path planning. His work addresses a critical gap in field robotics: enabling autonomous systems to operate safely in unstructured environments where traditional mapping and road markings are absent. Moore’s most-cited paper, “URA*: Uncertainty-aware Path Planning using Image-based Aerial-to-Ground Traversability Estimation for Off-road Environments” (2023), introduces a novel framework that integrates aerial imagery with ground-level perception to estimate terrain traversability while explicitly modeling sensing and perception uncertainty. This approach allows robots to plan safer, more reliable paths in challenging off-road settings, moving beyond classical methods that assume perfect environmental knowledge. Although early in his career—with 2 citations on this flagship work—Moore’s contributions are gaining traction for their practical impact on autonomous exploration, search-and-rescue, and agricultural robotics. His research bridges computer vision, probabilistic robotics, and path planning, offering a principled solution to one of the field’s most persistent obstacles. As autonomous systems venture into increasingly complex real-world terrains, Moore’s uncertainty-aware methodology stands out as a foundational step toward robust, trustworthy off-road navigation.
Research Focus
Key Achievements
Top Papers
- 1