Xijie Guo

Papers

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About

Xijie Guo’s research focuses on advancing robotic locomotion and dynamic control, with key contributions in parameter identification for manipulators and innovative legged robot design. In his most-cited work (2018, 9 citations), Guo introduced a novel method for identifying dynamic parameters of robot manipulators using Particle Swarm Optimization (PSO). By establishing a comprehensive dynamic model that includes friction and employing parameter transformation, his approach significantly improves the accuracy and efficiency of robot control—a critical step for high-performance industrial and service robotics. Earlier, Guo developed a hexapod robot featuring a passive joint on each foot (2017, 6 citations), drawing inspiration from insect biomechanics. This design enhances adaptability and stability on uneven terrain, showcasing his ability to bridge biological principles with practical engineering. Through these contributions, Guo has laid groundwork for more resilient and precisely controlled robotic systems, impacting fields from manufacturing to search-and-rescue. His work demonstrates a commitment to solving real-world challenges in robotics, making him a notable figure in the ongoing evolution of autonomous machines.