Edmanuel Cruz
Papers
7
Total Citations
37
H-Index
4
About
Edmanuel Cruz is a robotics researcher whose work centers on assistive social robotics, 3D perception, and semantic localization for autonomous systems. His most impactful contribution, "Geoffrey: An Automated Schedule System on a Social Robot for the Intellectually Challenged" (11 citations), addresses a critical societal need by developing a robot that helps intellectually challenged individuals and the elderly manage daily routines, reducing reliance on human overseers. Cruz also tackles fundamental perception challenges in robotics, notably improving the Pepper robot’s faulty depth sensing through monocular depth prediction and sensor fusion—methods detailed in two papers (7 citations each) that refine 3D perception for real-world deployment. His research on semantic localization, including training convolutional neural networks for dynamically learning robots (5 citations), enables machines to adapt to changing environments and recognize places using deep learning descriptors. Cruz’s work bridges human-robot interaction and computer vision, demonstrating how social robots can be both compassionate companions and technically robust. With a focus on long-term autonomy and knowledge adaptation, his contributions are paving the way for more intelligent, perceptive, and socially aware robots.
Research Focus
Key Achievements
Top Papers
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- 5Semantic Localization of a Robot in a Real Home3 citations · 2018
- 6Robot Semantic Localization Through CNN Descriptors2 citations · 2017
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