Max Robotics — Global Service Robot Directory + US Certification

About

Jingfan Zhang is a leading roboticist specializing in the design and control of wheel-legged robots, a class of machines that combine the speed of wheels with the agility of legs. Their work has fundamentally advanced how these hybrid robots maintain balance and execute agile locomotion in real-world environments. Zhang’s most influential contribution is the development of novel balance control strategies, including a linear feedback controller based on output regulation and LQR methods, which has garnered over 111 citations. They have also pioneered learning-based approaches, using reinforcement learning and adaptive dynamic programming to enable robots to balance without accurate dynamic models—a breakthrough cited more than 100 times. Zhang led the creation of the wheel-bipedal robot Ollie, demonstrating adaptive whole-body balance control, and the quadruped Max, which achieves multimodal agile locomotion. Their data-driven adaptive optimal output regulation technique addresses real-world challenges like unmodeled loads and motor imperfections. With over 300 total citations, Zhang’s work is essential reading for anyone interested in the future of mobile robotics, bridging theory and practice to create robots that can navigate complex terrains with unprecedented stability and efficiency.