Rongming Guo
Papers
2
Total Citations
20
H-Index
2
About
Rongming Guo is pioneering the intersection of formal logic and robotic locomotion, with a focus on making bipedal robots resilient to real-world disturbances. His core research areas include model predictive control (MPC), signal temporal logic (STL), and bipedal locomotion planning. Guo’s major contribution is the first-ever application of STL-guided trajectory optimization to bipedal walking, a breakthrough that provides formal guarantees for task completion while quantifying robustness against external perturbations. His 2024 paper, "Walking-by-Logic," has already garnered 13 citations, and its 2025 extension, "Robust-Locomotion-By-Logic," adds 7 more, reflecting growing interest in this novel framework. By integrating logical specifications directly into the control loop, Guo enables robots to reason about tasks like stepping over obstacles or maintaining balance under pushes—a significant step toward deploying humanoid robots in unpredictable environments. His work bridges formal methods and dynamic control, offering a principled path to safer, more reliable legged robots. For students and researchers, Guo’s research represents an exciting frontier where logic meets motion, promising to transform how we design resilient autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 2