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About

Chenglin Jing is a robotics researcher specializing in bipedal locomotion, with a particular focus on achieving stable, adaptive walking in complex environments. His work centers on the control of center of mass (CoM) trajectories and the development of advanced inverse kinematics algorithms. Jing’s most influential paper, “Stable walking of biped robot based on center of mass trajectory control” (2020, 6 citations), introduces a predictive control method that mimics how humans preemptively adjust their center of gravity to maintain balance. He has further advanced the field with fuzzy adaptive and improved algorithms for solving inverse kinematics (2010, 2022), addressing the computational challenges of real-time gait generation. Notably, his research extends to port environments, where he applied a human-simulated intelligent control (HSIC) approach to enhance a biped robot’s walking performance on uneven, coastal terrain (2020). While his citation counts are modest, Jing’s contributions are foundational for engineers seeking practical, robust control strategies for humanoid robots operating in unstructured settings.