Alexia Toumpa

Italian Institute of Technology, University of Patras, University of Leeds

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About

Alexia Toumpa is a robotics researcher whose work bridges the gap between perception, planning, and control for autonomous systems operating in unstructured environments. Her primary research areas include bipedal locomotion, autonomous navigation, and robot learning, with a particular focus on enabling robots to reason about and interact with complex, real-world terrain. Her most impactful contribution is a footstep planning system for bipedal robots that leverages curved contact patches to navigate rough terrain, a paper that has garnered 27 citations and addresses a critical bottleneck in legged locomotion: moving beyond flat-floor assumptions. Toumpa also developed a robust control system for line-following robots using Finite State Machine estimation, tackling the challenge of noisy sensor data in industrial and domestic settings. More recently, she has ventured into cognitive robotics with work on object-agnostic affordance categorization, using unsupervised graph embeddings to help robots understand how objects can be used—a step toward more intuitive human-robot collaboration. This trajectory from low-level control to high-level scene understanding marks Toumpa as a versatile researcher contributing to the foundational layers of autonomous robotics.