Chaoyue Guo

Papers

Total Citations

H-Index

About

Chaoyue Guo is a researcher advancing the frontiers of intelligent robotics and automated machinery, with a primary focus on exoskeleton systems and multi-objective control optimization. His most cited work, "FSM-HSVM-Based Locomotion Mode Recognition for Exoskeleton Robot" (2022, 13 citations), introduces a hierarchical support vector machine algorithm integrated with a finite state machine to achieve highly accurate and reliable locomotion mode recognition. By using hip joint angle data as input, this method significantly enhances the responsiveness and safety of wearable robotic exoskeletons—a critical contribution to assistive and rehabilitation technologies. More recently, Guo has tackled the complexity of industrial automation in his 2024 study on the 6-DOF robotic crusher, where he proposed a multi-objective optimal control method that simultaneously optimizes product quality, energy efficiency, output, and equipment wear. This work demonstrates his ability to address real-world engineering challenges through sophisticated mathematical modeling. With a growing citation record, Chaoyue Guo is establishing himself as a thoughtful innovator whose work bridges the gap between human-robot interaction and industrial process optimization.