Stavros Timotheatos

Czech Academy of Sciences, Institute of Computer Science

Papers

Total Citations

H-Index

About

Stavros Timotheatos is a roboticist whose research centers on humanoid locomotion, state estimation, and contact-aware control. His most cited work, “Unsupervised Gait Phase Estimation for Humanoid Robot Walking” (2019, 20 citations), tackles a fundamental challenge in bipedal robotics: determining the robot’s gait phase without relying on pre-labeled contact data. By introducing an unsupervised method that estimates gait phase directly from proprioceptive signals, Timotheatos enables more adaptive and robust walking controllers—critical for humanoids navigating unstructured environments. This contribution addresses a key gap in state estimation, where foot contact status is often assumed known but is rarely certain in practice. His work has implications for real-time control, reducing reliance on external sensors and improving autonomy. Timotheatos’ approach exemplifies a shift toward data-driven, model-free techniques in legged robotics, making his research valuable for students and engineers working on dynamic locomotion, sensor fusion, and machine learning for control. With a focus on practical, deployable solutions, his contributions help bridge the gap between simulation and real-world humanoid performance.