Zhenguo Tao

Papers

Total Citations

H-Index

About

Zhenguo Tao is advancing the frontier of hydraulic robotics, with a focus on biped locomotion, dexterous manipulation, and adaptive control. His most influential work, "Hierarchical jumping optimization for hydraulic biped wheel-legged robots" (2023, 23 citations), introduces a novel control framework that enables dynamic, energy-efficient jumping in hybrid wheeled-legged systems—a critical capability for navigating complex, unstructured terrains. This contribution addresses a long-standing challenge in legged robotics: balancing stability with agility under high-torque hydraulic actuation. Tao also led the design of the WLRG-I, a hydraulic-driven robotic gripper (2021, 9 citations), which demonstrates exceptional load-bearing capacity and robust grasping for industrial and assistive applications. His ongoing research into online learning model residual methods for force control (2025, 3 citations) promises to enhance real-time precision in hydraulic joints, reducing reliance on pre-calibrated models. With a cumulative impact of over 35 citations, Tao’s work bridges theoretical control theory and practical hardware design, offering scalable solutions for next-generation robots in disaster response, manufacturing, and human assistance. His achievements underscore a commitment to making hydraulic robots more versatile, resilient, and intelligent.