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About

Xiangjin Zeng is a leading researcher in robotics and automation, with a primary focus on adaptive control, visual servoing, and micro-manipulation systems. His most influential work, "Adaptive Task-Space Tracking Control of Robots Without Task-Space- and Joint-Space-Velocity Measurements" (2010, 77 citations), addresses a critical challenge in robotics: achieving precise task-space control without relying on potentially noisy velocity measurements. This contribution has been foundational for developing more robust and reliable robotic systems. Zeng has also made significant strides in uncalibrated visual servoing, as demonstrated in his work on SVM-based identification for micro-manipulation (18 citations) and his improved stability results for visual tracking using depth-independent interaction matrices (17 citations). His research extends to multi-robot systems, where he introduced novel frameworks for map building using Dezert-Smarandache theory (DSmT) to reduce computational and communication burdens. Zeng’s work on microscope visual servoing for micromanipulation robotic systems further highlights his expertise in applying advanced control techniques to precision tasks at the micro-scale. With a career dedicated to pushing the boundaries of robotic autonomy and precision, Xiangjin Zeng’s contributions continue to influence both theoretical advancements and practical applications in robotics.