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About

Yongling Fu is a distinguished researcher whose work lies at the intersection of robotics, intelligent systems, and mechanical design. His primary research areas include humanoid robot locomotion, teleoperation systems, and high-strength bearing mechanics for specialized robotic platforms. Fu’s most notable contribution is the development of an online walking pattern generation method for the humanoid robot BHR-2, published in 2006. This work, which has garnered 12 citations, introduced a novel approach that leverages key parameters from offline walking patterns—such as hip parameters, step length, and walking cycle—to enable real-time gait adaptation based on the Zero Moment Point (ZMP) criterion. This advancement significantly enhanced the stability and autonomy of bipedal locomotion. Fu has also made impactful strides in mechanical design, with a 2020 study on load distribution characteristics of planetary threaded roller bearings (5 citations), which supports the structural optimization of mountain-walking robotic platforms. His recent work includes a 2024 paper on master-slave teleoperation robot system design, reflecting his ongoing commitment to advancing human-robot interaction. With a total of over 30 citations across his publications, Fu’s research continues to influence both theoretical and applied robotics, particularly in the development of robust, adaptive systems for challenging environments.