Mrityunjay Jha

National Institute of Technology Rourkela

Papers

Total Citations

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About

Mrityunjay Jha is a robotics researcher whose work focuses on human-robot interaction, teleoperation, and motion recognition. His primary contributions lie in developing frameworks that enable robots to interpret and replicate human gestures, bridging the gap between human motion and robotic action. Jha’s most cited work, “Motion recognition using deep convolutional neural network for Kinect-based NAO teleoperation” (2022, 17 citations), introduces a deep learning approach that allows the NAO robot to recognize and reproduce human-like behavior through a Kinect sensor. This research enhances the capabilities of teleoperated robots by enabling them to act as extensions of human motion, with applications in assistive robotics and human-robot collaboration. His earlier paper, “NAO Robot Teleoperation with Human Motion Recognition” (2021, 9 citations), further explores this domain, demonstrating his sustained focus on intuitive robotic control. Jha’s work is notable for integrating convolutional neural networks with affordable sensor technology, making advanced teleoperation more accessible. His research has implications for rehabilitation, remote manipulation, and interactive robotics, positioning him as a promising contributor to the field of human-robot interaction.