Papers
11
Total Citations
180
H-Index
7
About
Stephanie Kemna is a robotics researcher whose work centers on autonomous underwater vehicles (AUVs), adaptive informative sampling, and multi-robot coordination. Her most influential contributions address a fundamental challenge in environmental monitoring: how to deploy teams of robots to collect maximally useful data about aquatic environments—such as algae concentrations and water temperature—while operating under real-world constraints like limited communication bandwidth. Her most cited work, "Multi-robot coordination through dynamic Voronoi partitioning" (2017, 65 citations), introduced an elegant approach for dividing exploration tasks among AUVs in communication-constrained settings, a problem with significant implications for ocean and lake monitoring. Subsequent research expanded this framework, investigating acoustic versus surface communication trade-offs, pilot survey strategies, and on-board feasibility of adaptive planning—demonstrating a sustained, systematic research program rather than isolated contributions. Notably, Kemna's career reveals an intriguing breadth: her early work on stroke rehabilitation user interfaces (2009, 21 citations) shows a foundation in human-centered design before her pivot to marine robotics. Across her body of work, her research has accumulated over 175 citations, underscoring genuine impact in the autonomous systems and environmental monitoring communities. Her contributions are particularly valuable to researchers designing scalable, intelligent robotic systems for real-world field deployment.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Developing a user interface for the iPAM stroke rehabilitation system21 citations · 2009
- 4
- 5Pilot Surveys for Adaptive Informative Sampling12 citations · 2018
- 6On-board Adaptive Informative Sampling for AUVs: a Feasibility Study9 citations · 2018
- 7
- 8
- 9
- 10