Alejandra Tabares
Papers
1
Total Citations
2
H-Index
1
About
Alejandra Tabares is an emerging researcher specializing in robotics, computer vision, and machine learning, with a particular focus on the intersection of sensor calibration and autonomous systems. Her most notable work, "Latent Space Representations for Marker-Less Realtime Hand–Eye Calibration" (2024), represents a significant contribution to the field of robot perception, addressing one of the fundamental challenges in robotic systems: accurately determining the spatial relationship between optical sensors and robotic manipulators without relying on traditional calibration markers. By leveraging latent space representations, Tabares and her collaborators developed an innovative approach that enables real-time calibration using single monocular cameras — low-cost, computationally efficient sensors that have historically struggled with this task due to inherent depth ambiguity. This work holds considerable practical value for deploying robots in unstructured, real-world environments where controlled calibration setups are impractical. Though her publication record is still growing, with her work already accumulating citations shortly after publication, Tabares demonstrates strong promise as a researcher pushing the boundaries of marker-less calibration techniques and making advanced robotic systems more accessible and adaptable across diverse application domains.
Research Focus
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Top Papers
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