Juhi Kumari
Papers
1
Total Citations
5
H-Index
1
About
Juhi Kumari is a researcher advancing the field of robotic manipulation and human-robot interaction, with a primary focus on grasp-pose prediction for hand-held objects. Her most-cited work, "Grasp-Pose Prediction for Hand-Held Objects" (2019), addresses a critical challenge in robotics: enabling machines to understand how humans naturally grasp and manipulate everyday items. By developing models that predict stable and functional grasp poses, Kumari’s research bridges the gap between computer vision and dexterous robotics, contributing to more intuitive and adaptive robotic systems. Though early in her career, her work has already garnered attention, with her key paper accumulating five citations—a meaningful start for a young researcher. This foundational study lays the groundwork for applications in assistive robotics, manufacturing, and virtual reality, where accurate grasp prediction is essential. Kumari’s contributions are particularly notable for their potential to enhance human-robot collaboration, making robotic assistants safer and more efficient in real-world environments. As she continues to build on this research, her insights into object manipulation and sensorimotor control promise to shape the next generation of intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Grasp-Pose Prediction for Hand-Held Objects5 citations · 2019