Papers
5
Total Citations
133
H-Index
3
About
Wenzhe Tong is a robotics researcher whose work pushes the boundaries of human-robot interaction and proprioceptive state estimation. His most impactful contribution is the development of a **robotic guide dog** that uses leash-guided hybrid physical interaction to lead visually-impaired individuals through narrow, cluttered spaces—a breakthrough that has garnered **102 citations**. This work addresses a critical gap in assistive robotics by moving beyond bulky wheeled platforms with rigid canes to a more natural, intuitive guidance system. Tong’s expertise extends to **state estimation for mobile robots**, where he has pioneered fully proprioceptive slip-velocity-aware methods using Invariant Kalman Filtering and Disturbance Observers (17 citations). He has also made notable advances in **tensegrity robotics**, designing a variable stiffness quasi-direct drive cable-actuated robot and developing proprioceptive state estimation with geometric constraints (8 and 3 citations, respectively). These contributions enable robots to navigate uncertain environments with greater autonomy and resilience. With a career spanning from early work on fuzzy logic for multi-robot coordination (1999) to cutting-edge tensegrity systems (2025), Tong’s research consistently addresses fundamental challenges in robot perception, control, and assistive technology.
Research Focus
Key Achievements
Top Papers
- 1Robotic Guide Dog: Leading a Human with Leash-Guided Hybrid Physical Interaction102 citations · 2021
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