Francisco Gomez‐Donoso
Papers
17
Total Citations
199
H-Index
7
About
Francisco Gomez-Donoso is a leading researcher at the intersection of computer vision, social robotics, and assistive technology. His work focuses on developing intelligent robotic systems that can perceive, understand, and interact with humans in meaningful ways. A key contribution is his development of accurate, monocular RGB-based 3D hand pose regression for robot hand teleoperation (45 citations), which enables intuitive control without expensive depth sensors. He also created the large-scale multiview 3D hand pose dataset (16 citations), a foundational resource for the field. In assistive robotics, Gomez-Donoso has made significant strides: he developed a robotic platform for customized rehabilitation of persons with disabilities (32 citations) and the HaReS hand motor skills rehabilitation system (7 citations). His work on the Geoffrey social robot (11 citations) introduces automated scheduling for intellectually challenged individuals, while his research on multimodal emotion recognition using the Pepper robot (10 citations) enhances human-robot interaction. By integrating semantic visual recognition into cognitive architectures (10 citations) and improving Pepper's 3D perception through depth prediction (7 citations), he advances robots' ability to function in ambient assisted living environments. His contributions directly impact the quality of life for elderly and disabled populations, with over 170 total citations demonstrating the influence of his work.
Research Focus
Key Achievements
Top Papers
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- 3Enhancing the Ambient Assisted Living Capabilities with a Mobile Robot27 citations · 2019
- 4Large-scale multiview 3D hand pose dataset16 citations · 2018
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- 7Semantic visual recognition in a cognitive architecture for social robots10 citations · 2020
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