Duarte Moutinho
Papers
2
Total Citations
51
H-Index
2
About
Duarte Moutinho is a researcher at the forefront of intelligent manufacturing and human-robot collaboration. His work centers on integrating deep learning and advanced control systems to make industrial robots more adaptive and context-aware. Moutinho’s most cited paper, “Deep learning-based human action recognition to leverage context awareness in collaborative assembly” (2022, 49 citations), demonstrates how neural networks can enable robots to interpret human gestures and movements in real time, fostering safer and more efficient shared workspaces. Complementing this, his work on “Force control heuristics for surpassing pose uncertainty in mobile robotic assembly platforms” (2021) addresses a critical challenge in flexible automation: overcoming positional errors in unstructured environments. By applying force control to a mobile manipulator assembling an internal combustion engine, he showed how robots can physically adapt to uncertainty without costly precision fixtures. Though his citation count is still growing, Moutinho’s contributions are notable for bridging the gap between theoretical AI and practical industrial deployment. His research offers a clear vision of future factories where mobile robots and human workers collaborate seamlessly, guided by perception and compliant interaction.
Research Focus
Key Achievements
Top Papers
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