Arnab Paikaray

National Institute of Technology Rourkela

Papers

Total Citations

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About

Arnab Paikaray is a researcher whose work sits at the intersection of robotics, computer vision, and human-robot interaction. His primary focus is on enabling more intuitive and human-like teleoperation of robots, particularly through motion recognition and deep learning. His most cited paper, "Motion recognition using deep convolutional neural network for Kinect-based NAO teleoperation" (2022, 17 citations), introduces a framework that allows a NAO robot to recognize and replicate human motions captured by a Kinect sensor. This work is notable for bridging the gap between human movement and robotic action, using deep convolutional neural networks to interpret complex gestures in real time. By empowering robots to understand and act upon human motion, Paikaray’s research contributes directly to more natural, accessible human-robot collaboration. His work holds significant promise for assistive robotics, rehabilitation, and interactive automation, where seamless teleoperation is key. With a growing citation footprint, Arnab Paikaray is establishing himself as a contributor to the next generation of intelligent, responsive robotic systems.