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About

Pengfei Xiao is a robotics researcher whose work focuses on advancing the precision and autonomy of industrial and space manipulators. His primary research areas include robot calibration, task planning, and trajectory optimization for complex maintenance operations. Xiao’s most significant contribution is a novel fixed axis-invariant calibration approach that improves the absolute positioning accuracy of industrial manipulators by simplifying the modeling process and enhancing calibration effectiveness—a method that has garnered 26 citations and addresses a longstanding challenge in robotics. In the domain of space robotics, he has developed a modified clustering method for task planning of large-scale space solar power stations, enabling efficient on-orbit maintenance. His trajectory optimization algorithms for 7R robots and Cartesian point-to-point planning under jerk constraints tackle critical issues of stability, base disturbance, and joint variation in space environments. With a total of 48 citations across his most-cited papers, Xiao’s work is instrumental in making space maintenance operations more reliable and efficient, bridging the gap between theoretical robotics and practical deployment in extreme environments.