Chelsey Edge
Papers
4
Total Citations
39
H-Index
3
About
Chelsey Edge is a robotics researcher whose work bridges the gap between autonomous systems and human-robot interaction in challenging underwater environments. Her primary research areas include underwater computer vision, field robotics, and human-robot collaboration. Edge made a foundational contribution with the creation of the Semantic Segmentation of Underwater IMagery (SUIM) dataset—the first large-scale, pixel-annotated benchmark for underwater scenes, featuring eight object categories including fish, reefs, and robots. This work, with 17 citations, has become a key resource for advancing underwater perception. She also developed the LoCO AUV, a low-cost, open-source autonomous underwater vehicle rated to 100 meters, designed for single-person deployment and vision-guided tasks. In human-robot interaction, Edge proposed a motion-based communication system for field robots and introduced the Diver Interest via Pointing (DIP) algorithm, which enables AUVs to interpret diver pointing gestures using only a monocular camera. Her work on robot communication via motion (16 citations) has been particularly influential. Edge’s contributions are advancing the practicality and accessibility of underwater robotics for scientific exploration and collaborative tasks.
Research Focus
Key Achievements
Top Papers
- 1Semantic Segmentation of Underwater Imagery: Dataset and Benchmark17 citations · 2020
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- 4Diver Interest via Pointing: Human-Directed Object Inspection for AUVs2 citations · 2023