Karim Abdelatty

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About

Karim Abdelatty is a robotics researcher specializing in autonomous navigation, multi-robot collaboration, and Bayesian decision-making for field robotics. His work bridges aerial and ground systems to enhance real-time environmental perception and precision operation in unstructured outdoor settings. In his highly cited 2018 paper, "Online Aerial Terrain Mapping for Ground Robot Navigation," Abdelatty introduced a collaborative unmanned aerial and ground vehicle framework that enables the aerial platform to capture and classify terrain imagery into orthomosaics, which then inform the ground robot’s path planning in real time. This work has garnered 42 citations, reflecting its impact on integrated aerial-ground autonomy. Additionally, his paper "Multistage Bayesian Autonomy for High‐Precision Operation in a Large Field" presents a generalized multistage Bayesian framework that allows robots to perform high-precision tasks on static targets across expansive environments, addressing the challenge of operational accuracy at scale. Through these contributions, Abdelatty has advanced the practical deployment of autonomous systems in agriculture, surveying, and search-and-rescue, demonstrating how probabilistic reasoning and sensor fusion can enable robust, field-ready robotic performance.