Max Robotics — Global Service Robot Directory + US Certification

About

Zhe Tang is a pioneering researcher in humanoid robotics, with a primary focus on bipedal locomotion and gait planning. His work addresses fundamental challenges in achieving stable, natural, and efficient walking for humanoid robots. Tang’s most influential contribution is his trajectory planning method for smooth biped robot transitions, which uses third-order spline interpolation to minimize instant velocity changes during swing leg-ground collisions—a critical issue for stable walking. This work, published in 2004, has garnered 29 citations, highlighting its foundational impact. He also developed methods for 3-dimensional walking reference trajectory generation and introduced the Relative-ZMP (R-ZMP) concept for gait synthesis, advancing motion planning for high-degree-of-freedom systems. Additionally, Tang explored dynamic fuzzy neural networks to model humanoid robotics, addressing nonlinearity and variable mechanical structures. His research has been instrumental in enabling soccer-playing humanoid robots, demonstrating practical applications in dynamic environments. With a career spanning key contributions to trajectory optimization and gait synthesis, Zhe Tang remains a notable figure in humanoid robotics, inspiring further innovations in autonomous locomotion.