Atilla Baskurt

Institut National des Sciences Appliquées de Lyon, Université Claude Bernard Lyon 1

Papers

Total Citations

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About

Atilla Baskurt is a researcher whose work sits at the intersection of robotics, computer vision, and machine learning, with a particular focus on enabling intelligent agents to perceive, navigate, and understand dynamic environments. His most cited work, "Multi-Object Navigation in real environments using hybrid policies" (2023, 6 citations), tackles a critical challenge in robotics: moving beyond classical SLAM and waypoint planning to incorporate high-level visual reasoning. This research proposes hybrid policies that allow robots to navigate real-world spaces while interacting with multiple objects, bridging the gap between simulated environments and practical deployment. In his earlier work, "Action recognition in videos" (2012, 4 citations), Baskurt addressed the foundational problem of identifying human activities from motion data—a capability essential for video surveillance, robotics, and video indexing. While his citation counts reflect an emerging career, the breadth of his contributions—from action recognition to multi-object navigation—demonstrates a sustained commitment to advancing autonomous systems that can reason about and act within complex, unstructured environments.