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About

Zejun Hong is a robotics researcher specializing in legged locomotion, motion planning, and control for complex robotic systems. His work spans wheeled-bipedal robots, quadrupedal robots, and bipedal running, with a focus on bridging the gap between theoretical frameworks and real-world autonomous mobility. Hong's most influential contribution is his hierarchical motion planning and control framework for jumping in wheeled-bipedal robots, published in 2020 and garnering nearly 100 citations — a testament to its significance in a rapidly evolving field. By tackling the inherent underactuation challenges of hybrid wheeled-legged designs, this work opened new avenues for agile robot locomotion. His 2021 research on perceptive autonomous stair climbing for quadrupeds (26 citations) demonstrated practical advances in perception-driven control, meaningfully expanding the operational scope of legged robots in real-world environments. Further broadening his contributions, Hong investigated quadruped push recovery using switched-systems theory (23 citations) and developed a differentially flat SLIP-based framework for three-dimensional bipedal running. Collectively, his research reflects a rigorous and versatile approach to robot dynamics and control, making his work essential reading for students and researchers pursuing robust, agile autonomous systems.