Yash Jogi
Papers
1
Total Citations
2
H-Index
1
About
Yash Jogi is a robotics researcher whose work focuses on making human-robot interaction more intuitive and accessible. His primary research areas include vision-based gesture control, robotic manipulation, and human-robot interfaces. Jogi’s most notable contribution is his work on the "Teach Pendant at Fingertips" system, which uses vision-based gesture-driven control to operate the Dexter ER2 robotic arm. This innovation addresses a critical challenge in robotics: the unintuitive nature of traditional teach pendants, which require substantial training to use effectively. By enabling operators to control robotic arms through natural hand gestures, Jogi’s approach significantly lowers the barrier to entry for robotic programming and operation. His work has already garnered attention, with his 2025 paper receiving 2 citations in its early stages, signaling growing interest in his methods. Jogi’s research holds promise for applications in manufacturing, education, and assistive robotics, where intuitive control systems can enhance productivity and accessibility. His contributions represent an important step toward bridging the gap between human intent and robotic action, making advanced robotic systems more user-friendly for non-experts.
Research Focus
Key Achievements
Top Papers
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