Svetlana Seliunina
Papers
1
Total Citations
1
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About
Svetlana Seliunina is a robotics researcher specializing in 3D perception, person detection, and human-robot interaction, with a particular focus on LiDAR-based sensing systems. Her work addresses the critical challenge of enabling robots to safely perceive and interact with people in their surroundings using non-traditional sensor configurations. In her most-cited paper, "Person Segmentation and Action Classification for Multi-Channel Hemisphere Field of View LiDAR Sensors" (2025), she developed a novel approach for segmenting persons and classifying their actions directly from 3D scans captured by hemisphere field-of-view LiDAR sensors, such as the Ouster OSDome-64. This work is notable for creating a dedicated dataset and demonstrating that wide-angle LiDAR can effectively support both person detection and action recognition—a key capability for autonomous robots operating in close proximity to humans. While her citation count is still growing, Seliunina’s research is positioned at the intersection of sensor innovation and practical robotics, contributing to safer, more perceptive autonomous systems. Her work holds promise for applications in service robotics, collaborative manufacturing, and autonomous navigation in crowded environments.
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Top Papers
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