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About

Qiankun Zhao is a robotics researcher whose work centers on the design, control, and precision of advanced robotic manipulators, with a particular focus on addressing the challenges of backlash, flexibility, and disturbance in multi-joint systems. His major contributions include the development of the D-Arm, a novel seven-degree-of-freedom (7-DOF) robotic manipulator that employs dual-motor anti-backlash control technology to mitigate the coupling of nonlinear backlash with unknown disturbances. Zhao has also pioneered calibration methods to predict and compensate for flexible positioning errors caused by end-effector gravity in compliant series robots, significantly improving absolute positioning accuracy. His work on linear active disturbance rejection control for dual-motor coaxial driving joints and observer-based finite-time prescribed performance sliding mode control further demonstrates his systematic approach to enhancing motion performance under uncertainties and disturbances. With his most-cited paper, "Cross-modal attention fusion network for RGB-D semantic segmentation," accumulating 44 citations, Zhao’s research bridges mechanical design and intelligent control, making notable strides in both theoretical robustness and practical implementation for robotic systems.