Papers
5
Total Citations
42
H-Index
3
About
Yunxi Tang is a roboticist whose research centers on dynamic control, underactuated systems, and bio-inspired locomotion for legged and manipulator robots. His most cited work, “Dynamic Visual Tracking for Robot Manipulator Using Adaptive Fading Kalman Filter” (20 citations), addresses the challenge of maintaining visual tracking during temporary occlusion, introducing a robust estimation method that improves real-time robot control. Tang has also made notable contributions to safe landing for quadruped robots, as seen in his 2023 paper on a 3-DoF morphable inertial tail (14 citations), which draws inspiration from the “falling cat problem” to enable aerial reorientation and impact mitigation. His work on operational space control for underactuated manipulators, using orthogonal projection and quadratic programming, provides a novel framework for controlling systems with fewer actuators than degrees of freedom. Tang further advanced trajectory optimization with the hybrid multiple-shooting DDP method (HM-DDP), offering a computationally efficient solver for constrained motion planning. His development of a portable hybrid Pendubot-Acrobot platform demonstrates a commitment to accessible, hands-on robotics education. With a growing citation impact and a focus on bridging theory and practice, Tang’s research is shaping the future of agile, adaptive robotic systems.
Research Focus
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Top Papers
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