Ziqi Gao
Papers
1
Total Citations
5
H-Index
1
About
Dr. Ziqi Gao is a rising scholar in robotics and intelligent manufacturing, whose work centers on enhancing robotic manipulation precision through advanced calibration and optimization techniques. Their most notable contribution is the development of posture-sequence particle swarm optimization (PS2O), a novel algorithm for tool center point (TCP) calibration introduced in their 2023 paper. This method addresses a critical bottleneck in industrial robotics—the accuracy of TCP, which directly governs a robot's ability to perform precise tasks. By innovatively integrating the condition number and minimum eigenvalue of the regression matrix into the optimization framework, Dr. Gao’s approach significantly improves calibration reliability and efficiency. Though early in their career, with their flagship paper already garnering 5 citations, the work signals strong potential for impact in automation and robotics communities. Dr. Gao’s research bridges theoretical optimization with practical manufacturing challenges, offering a scalable solution for high-precision robotic systems. As their citation count grows, they are poised to become a key contributor to the field of robot calibration and intelligent control.
Research Focus
Key Achievements
Top Papers
- 1