Md Jamal Ahmed Shohan
Papers
1
Total Citations
10
H-Index
1
About
Md Jamal Ahmed Shohan is a researcher whose work lies at the intersection of robotics, computer vision, and human-machine interaction. His most-cited paper, "Real time hand movement controlled robotic arm for risk prevention" (2017), introduces an innovative "Artificial Human Hand Model" that uses webcam-based image processing to precisely replicate human hand movements. By relying on visual input rather than sensors, this system avoids sensor noise and damage, offering a more adjustable and reliable response for risk prevention in hazardous environments. This work has garnered 10 citations, reflecting its relevance in the field of assistive and safety robotics. Shohan’s contributions demonstrate a practical approach to bridging human intent and robotic action, with potential applications in industrial safety, remote manipulation, and prosthetics. His research highlights the importance of cost-effective, vision-based control systems that enhance both precision and safety. For students and researchers exploring gesture-controlled robotics or human-robot collaboration, Shohan’s work offers a compelling example of how accessible technology can be harnessed to create impactful, real-world solutions.
Research Focus
Key Achievements
Top Papers
- 1Real time hand movement controlled robotic arm for risk prevention10 citations · 2017