Di Zu

About

Di Zu is a pioneering researcher in the field of robotics, with a focus on dynamic stability and intelligent trajectory generation for mobile and humanoid systems. Her early work on wheel-based humanoid robots introduced a novel integration of the Recursive Newton-Euler method with the Zero Moment Point (ZMP) concept, enabling precise dynamic stability analysis—a critical advancement for ensuring safe locomotion in hybrid robotic platforms. This foundational paper, with 11 citations, remains a reference for researchers bridging wheeled and bipedal designs. Zu further advanced autonomous navigation through her innovative use of Mixed-Integer Linear Programming (MILP) in Relative Velocity Coordinates (RVCs), a method that elegantly solves the nonlinear constraints of obstacle avoidance and target pursuit in dynamic environments. Garnering 5 citations, this work demonstrates her ability to transform complex control problems into computationally tractable solutions. Together, these contributions highlight Zu’s talent for merging rigorous mathematical modeling with practical robotic applications, making her a notable figure in the evolution of agile, stable, and intelligent robotic systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Dynamic Stability Analyses Based on ZMP of a Wheel-based Humanoid Robot

   11 citations · 2006
2. 2
   MILP-based trajectory generation in Relative Velocity Coordinates

   5 citations · 2007

Key Collaborators

Contact & Links