Roxana Leontie
Papers
1
Total Citations
2
H-Index
1
About
Roxana Leontie is a researcher specializing in robotics, proprioceptive sensing, and adaptive control systems. Her work focuses on enhancing robotic manipulation through sensor-driven load equalization, a critical area for improving the efficiency and stability of multi-armed robots in dynamic environments. Her most-cited paper, "Load Equalization on a Two-Armed Robot via Proprioceptive Sensing" (2013), introduces a novel approach that leverages internal force feedback to balance payloads between robotic arms without external sensors. This contribution has garnered 2 citations, reflecting its foundational role in advancing proprioceptive techniques for cooperative robotics. Leontie’s research bridges the gap between theoretical control algorithms and practical robotic applications, offering insights into how robots can autonomously adapt to varying loads—a key challenge in industrial automation and human-robot collaboration. Her work is particularly notable for its emphasis on simplicity and robustness, avoiding reliance on costly external sensing infrastructure. For students and researchers exploring sensorimotor control or multi-agent robotic systems, Leontie’s contributions provide a compelling example of how proprioceptive data can transform robotic adaptability, laying groundwork for future innovations in autonomous manipulation.
Research Focus
Key Achievements
Top Papers
- 1Load Equalization on a Two-Armed Robot via Proprioceptive Sensing2 citations · 2013