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About

Daoguo Yang is a robotics researcher whose work sits at the intersection of industrial automation, kinematic modeling, and advanced manufacturing. His research focuses on enabling smarter, more precise robotic systems for Industry 4.0 environments, particularly through real-time monitoring and control. Yang’s most cited work, “Online Monitoring & Controlling Industrial Arm Robot Using MQTT Protocol” (35 citations), addresses the critical need for seamless communication in modern industrial management systems. He has also made foundational contributions to kinematic modeling, as seen in his study of the UR10 robot using Denavit-Hartenberg parameters and screw theory (17 citations). More recently, Yang has tackled complex challenges in laser cladding repair, developing a smooth path generation method for irregular worn surfaces using 3D point cloud measurement. His work on calibrating dual industrial robot systems through hand-eye calibration algorithms further advances collaborative robotics for precision tasks like drill bit repair. By integrating teleoperation protocols such as XMPP for cloud-based control, Yang is pushing the boundaries of how robots can operate in dangerous or hard-to-reach environments. His research is particularly valuable for students and engineers interested in the practical intersection of robotics, sensor integration, and industrial automation.