Papers
19
Total Citations
347
H-Index
10
About
Theodoros Stouraitis is a robotics researcher whose work spans manipulation planning, multi-robot collaboration, and human-robot interaction, with a particular focus on making robotic systems more capable, adaptive, and intelligent in complex real-world environments. His early contributions to reachability and capability analysis (2013, 64 citations) laid foundational groundwork for understanding what robots can physically achieve, while his pioneering research on dyadic collaborative manipulation introduced principled optimization frameworks for human-robot and robot-robot joint planning tasks. His bilevel optimization approach for online hybrid motion planning (2020, 53 citations) and decentralized ability-aware adaptive control for multi-robot teams (2021, 55 citations) represent landmark contributions to coordinated manipulation, addressing the profound challenges of heterogeneous robot collaboration under limited communication. Stouraitis has also advanced the frontiers of dynamic manipulation, tackling impact-aware catching of large-momentum objects and non-prehensile manipulation through complementarity-constrained trajectory optimization. More recently, his work on augmented reality-based human-robot training and adaptive assistive robotics frameworks reflects a broader vision for accessible, explainable robotic systems. With over 300 cumulative citations, his research consistently bridges theoretical rigor with practical impact across manipulation, autonomy, and collaborative robotics.
Research Focus
Key Achievements
Top Papers
- 1Reachability and Capability Analysis for Manipulation Tasks64 citations · 2013
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- 5Explainable Human-Robot Training and Cooperation with Augmented Reality22 citations · 2023
- 6Impact-Aware Bimanual Catching of Large-Momentum Objects21 citations · 2024
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- 10Dyadic collaborative Manipulation through Hybrid Trajectory Optimization.13 citations · 2018