Yanling Guo

Northeast Forestry University, Xi'an Railway Survey and Design Institute

Papers

Total Citations

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About

Yanling Guo is a robotics researcher whose work centers on the locomotion and control of quadruped robots, particularly for navigating complex and uneven terrain. Her most significant contribution lies in developing a hierarchical control framework for static gait planning, which enables quadruped robots to walk stably on rough surfaces. This approach, detailed in her highly cited 2019 paper (14 citations), separates the problem into high-level trajectory planning for the robot’s center of mass and low-level gait generation, improving both efficiency and robustness. Guo further advanced this field by learning cost functions for optimal foothold selection, integrating Denavit–Hartenberg modeling and Time-of-Flight camera data to enhance real-world adaptability (5 citations). Her earlier work on serial communication interfaces for microcontroller-based robots (4 citations) demonstrates a foundational expertise in embedded systems. With a total of over 20 citations across her key publications, Guo’s research bridges theoretical control algorithms and practical robotic hardware, offering scalable solutions for legged locomotion in unstructured environments. Her work is particularly valuable for students and engineers interested in field robotics, motion planning, and the integration of perception with control.