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About

Linzhu Yue is a robotics researcher whose work spans two distinctive yet complementary domains: legged robot locomotion and construction automation. In the field of quadrupedal robotics, Yue has made significant contributions to motion planning and control, developing an optimal framework for generating energy-efficient jumping motions — including flips and spins — by formulating complex centroidal dynamics as a black-box optimization problem (23 citations). His work on generalized locomotion controllers (GenLoco) addresses the growing need for versatile, transferable control policies across commercially available quadrupedal platforms (17 citations), while his adaptive Model Predictive Control research tackles the persistent gap between simplified robot models and real-world performance. In construction robotics, Yue has pioneered autonomous solutions for labor-intensive interior tasks, including a BIM-integrated wall painting system (18 citations) and vision-based impedance controllers for robotic wall polishing (15 citations). His adaptive control work for rope-climbing robot manipulators further demonstrates his ability to solve challenging real-world deployment problems. With a research portfolio accumulating nearly 100 citations, Yue represents an emerging voice bridging advanced legged locomotion and practical construction automation.