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About

David Meger is a robotics and computer vision researcher whose work spans autonomous perception, semantic spatial modeling, underwater robotics, and multi-modal object understanding. He is perhaps best known for the "Curious George" platform, an attentive semantic robot system that pioneered integrated visual search capabilities in mobile robots, garnering 167 citations and establishing a benchmark for real-world object recognition beyond static image databases. His early contributions also include simultaneous planning, localization, and mapping within camera sensor networks, and informed visual search methods that combined attention mechanisms with object recognition to enable robots to intelligently navigate cluttered environments. Meger's research expanded significantly into marine robotics, where he developed frameworks for legged underwater robots capable of learning swimming gaits autonomously from experience and executing precise 3D trajectory control — work with meaningful implications for ocean exploration and coral reef health assessment using automated image analysis. More recently, his 2020 paper on 3D shape reconstruction from combined vision and touch signals reflects a growing interest in multi-sensory robot perception, drawing inspiration from human developmental learning. Across more than a decade of contributions, Meger's cumulative citation record demonstrates sustained influence in making robots smarter, more adaptive, and capable of understanding complex real-world environments with increasing autonomy.