Elvira Chebotareva
Papers
19
Total Citations
136
H-Index
7
About
Elvira Chebotareva is a robotics researcher whose work spans human-robot interaction, autonomous mobile robotics, and collaborative manufacturing systems. Her research addresses one of the field's most pressing challenges: enabling seamless, safe cooperation between humans and robots in real-world environments. With over 110 cumulative citations across her most notable works, Chebotareva has established herself as a productive contributor to applied robotics research. Her most cited work (23 citations) examines prospective human-robot interaction scenarios in collaborative manufacturing, while her parallel investigations into sensor fusion — combining laser rangefinders with monocular cameras for human-following algorithms — demonstrate her strong technical depth in robot perception. These studies, each garnering 16 citations, have informed practical mobile robot deployments using platforms like PMB-2 and TIAGo Base. Chebotareva has also advanced gesture-controlled collaborative robotics, conducting pilot experiments with the UR5e manipulator that explore intuitive, vision-based human control interfaces. Her contributions extend to simulation infrastructure, including an open-source Gazebo human model library, and to robotics education through an accessible Arduino-Raspberry Pi balancing robot curriculum. Taken together, her body of work reflects a commitment to bridging laboratory innovation with practical, human-centered robotic applications.
Research Focus
Key Achievements
Top Papers
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- 6Open Source Library of Human Models for Gazebo Simulator7 citations · 2022
- 7Camera-based safety system for collaborative assembly7 citations · 2024
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- 9Emotional Social Robot "Emotico"6 citations · 2019
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