Eivind Meyer
Papers
2
Total Citations
92
H-Index
2
About
Eivind Meyer is a researcher specializing in autonomous navigation, marine robotics, and artificial intelligence-driven guidance systems, with a particular focus on unmanned surface vehicles (USVs). His work sits at the intersection of deep reinforcement learning and maritime autonomy, addressing some of the most fundamental challenges in robotic guidance: path following and collision avoidance. Meyer's most influential contribution is his development of COLREG-compliant collision avoidance systems for USVs using deep reinforcement learning — a significant advancement in ensuring that autonomous vessels can navigate safely while adhering to internationally recognized maritime rules of the road (COLREGs). This work, published in 2020, has garnered over 89 citations, reflecting its strong resonance within the autonomous systems and maritime engineering communities. By applying modern machine learning techniques to a domain long dominated by classical rule-based approaches, Meyer helped push the field toward more adaptive, scalable, and practically deployable solutions. His research is particularly valuable for students and engineers working on autonomous marine systems, as it bridges theoretical reinforcement learning with real-world regulatory constraints — a critical step toward the safe deployment of fully autonomous vessels in shared maritime environments.
Research Focus
Key Achievements
Top Papers
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- 2