ZHAO Changxi

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About

Zhao Changxi’s research focuses on advancing the positioning accuracy and real-time control of industrial mobile robots, particularly for large-scale, complex component machining. His major contribution lies in developing a novel real-time compensation strategy that integrates industrial CNC systems with robotic control architectures. By employing Latin hypercube sampling to optimize joint space sampling points and constructing a multivariate nonlinear mapping model between joint space and end-effector position errors, Zhao significantly improves the precision of robot tool center point (TCP) positioning. His work demonstrates that this method effectively reduces positioning errors across various poses within the robot’s workspace, validated through linear interpolation trajectory tests. With his most-cited paper accumulating 3 citations, Zhao’s research addresses a critical bottleneck in mobile robot machining—balancing real-time performance with high accuracy. His achievements include the successful implementation of TCP error compensation on commercial CNC systems, showcasing practical applicability. For students and researchers in robotics and precision manufacturing, Zhao’s work offers a robust framework for enhancing the reliability of mobile robots in high-stakes industrial environments, bridging the gap between theoretical modeling and real-world deployment.