Reagan Tibbetts
Papers
1
Total Citations
7
H-Index
1
About
Reagan Tibbetts is a robotics researcher whose work focuses on enabling autonomous navigation in some of the most challenging environments on Earth: underwater caves. Their key contributions lie at the intersection of computer vision, field robotics, and weakly supervised learning. Tibbetts’ most cited work, “Weakly Supervised Caveline Detection for AUV Navigation Inside Underwater Caves” (2023), tackles the critical problem of autonomous cave mapping—a task that is traditionally time-consuming, labor-intensive, and hazardous for human divers. By developing a method for caveline detection that requires minimal labeled data, Tibbetts has advanced the feasibility of using Autonomous Underwater Vehicles (AUVs) for mapping these complex, visually degraded environments. This research has direct implications for water resource management, hydrogeology, and historical studies. With 7 citations on their leading paper, Tibbetts is establishing a strong foundation for future work in robust, perception-driven autonomy. Their research represents a meaningful step toward safer, more efficient exploration of Earth’s hidden underwater landscapes, making them a promising voice in the field of field and marine robotics.
Research Focus
Key Achievements
Top Papers
- 1