Dezhou Zhang

Nanjing University of Posts and Telecommunications

Papers

Total Citations

H-Index

About

Dezhou Zhang is a researcher specializing in robotics, human-robot interaction, and motion imitation, with a focus on bridging the gap between human actions and robotic execution. His major contributions lie in developing algorithms and control systems that enable robots to replicate complex human motions in real time, addressing the physical and computational challenges posed by the differences between human and robotic anatomy. His most cited work, "Work chain-based inverse kinematics of robot to imitate human motion with Kinect" (2018, 11 citations), proposes a novel approach using a work chain framework to achieve accurate human motion imitation via depth-sensing cameras, advancing the field of artificial intelligence-driven robotics. Additionally, his paper "Real Time Writing Reproduction by Robot Arm" (2018, 2 citations) tackles the challenge of enabling robots to write dynamically, moving beyond predefined motion inputs to real-time reproduction. Zhang’s research has practical implications for assistive robotics, manufacturing, and interactive systems, demonstrating how robots can learn from and adapt to human behavior. His work is a stepping stone toward more intuitive and responsive robotic systems, making him a notable contributor to the robotics community.