Xiaogang Song
Papers
6
Total Citations
63
H-Index
4
About
Xiaogang Song is a robotics researcher specializing in the design, kinematics, and control of hyper-redundant and parallel robots, with a focus on bionic manipulation and precision manufacturing. His most cited work introduces a hyper-redundant elephant’s trunk robot with an open structure, addressing complex tasks in constrained, obstacle-rich environments (23 citations). Song has made significant contributions to robot control theory, including dynamic feedforward control in decoupling space for parallel robots (19 citations) and a PD computed torque control method with online self-gain tuning (9 citations), both enhancing accuracy and robustness. His research extends to coupled force–position control for dynamic contact force tracking in uncertain environments, critical for industrial assembly and grinding (4 citations). Song also explores skill acquisition in multi-robot precision assembly using cooperative compliant control and accurate dynamic model identification via double-encoder compensation, advancing high-precision manufacturing. His work bridges theoretical control methods and practical robotic applications, demonstrating impact in bionic design, parallel robotics, and industrial automation.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6