Deepak Paramkusam
Papers
1
Total Citations
41
H-Index
1
About
Deepak Paramkusam is a robotics researcher whose work centers on human-robot interaction, motion imitation, and intelligent control systems for humanoid platforms. His most cited contribution, "Inverse kinematics of a NAO humanoid robot using kinect to track and imitate human motion" (2015, 41 citations), presents a pioneering approach to enabling robots to replicate human upper-body movements in real time. In this study, Paramkusam implemented and compared three distinct methods—direct angle mapping, inverse kinematics using fuzzy logic, and iterative Jacobian-based inverse kinematics—using a Kinect sensor for motion capture. This work demonstrated how low-cost, accessible sensors could be leveraged for sophisticated robotic control, advancing the field of teleoperation and assistive robotics. His comparative analysis of these techniques provided a practical roadmap for researchers seeking to balance computational efficiency with motion accuracy. Beyond this flagship paper, Paramkusam’s research has implications for rehabilitation robotics, humanoid design, and autonomous systems that learn from human demonstration. His contributions continue to influence students and engineers working on intuitive, human-like robotic interfaces, making him a notable figure in the growing intersection of computer vision and robotics.
Research Focus
Key Achievements
Top Papers
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