Papers
2
Total Citations
22
H-Index
2
About
Jiaxiang Xu is a robotics researcher whose work focuses on the control and optimization of robotic systems, particularly exoskeletons and industrial manipulators. His key contributions lie in developing advanced control strategies and trajectory planning algorithms to enhance robot performance, efficiency, and safety. In his highly cited 2021 paper, Xu introduced an M-G modal space sliding mode control for lower limb exoskeleton robots driven by electrical actuators, a novel approach that improves stability and precision in human-robot interaction. This work has garnered 14 citations, reflecting its impact on rehabilitation and assistive robotics. His 2020 study on time-optimal trajectory planning for industrial robots, which integrates an improved particle swarm optimization algorithm with golden section search, has been cited 8 times and addresses critical challenges in manufacturing—reducing energy consumption and cycle times while boosting productivity. Xu’s research bridges theoretical innovation and practical application, offering solutions that are both computationally efficient and robust. His achievements underscore a commitment to advancing robotic autonomy and human-robot collaboration, making his work essential reading for students and researchers in control systems, optimization, and mechatronics.
Research Focus
Key Achievements
Top Papers
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- 2