Stephen Krauss
Papers
2
Total Citations
12
H-Index
2
About
Stephen Krauss is a researcher at the forefront of marine robotics, specializing in autonomous underwater vehicle (AUV) navigation and perception. His work focuses on two critical challenges: enabling reliable underwater communication and developing cost-effective collision avoidance systems. Krauss’s most cited paper, “Model-based learning of underwater acoustic communication performance for marine robots” (2021, 10 citations), introduces a novel framework that predicts acoustic communication quality in real-time, allowing AUVs to adapt their behavior for more robust data transmission in challenging underwater environments. This contribution is foundational for long-duration, cooperative robotic missions. In his more recent work, “Use of a low-cost forward-looking sonar for collision avoidance in small AUVs, analysis and experimental results” (2023, 2 citations), Krauss demonstrates a practical, beam-limited sonar system paired with a tailored avoidance strategy, proving that safe navigation is achievable without expensive hardware. This work is particularly impactful for the growing field of low-cost, accessible marine robotics. Through these contributions, Krauss is helping to make autonomous underwater systems more intelligent, reliable, and deployable for scientific exploration and industrial inspection.
Research Focus
Key Achievements
Top Papers
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- 2