Papers
6
Total Citations
81
H-Index
6
About
Bosheng Ye is a leading researcher in industrial robotics, specializing in data-driven control, motion planning, and precision automation. His work addresses critical challenges in robot performance, including speed tracking, path control, and force-position coordination. Ye’s most impactful contribution is the development of an iterative data-driven fractional model reference control for repetitive speed tracking in industrial robots, a method that bypasses the need for explicit system models and has garnered 24 citations. He also pioneered a robust cascade path-tracking control using constrained iterative feedback tuning, cited 23 times, which enhances position accuracy under disturbances. His research extends to adaptive impedance control for robot contact with inclined planes, dynamic modeling via improved particle swarm optimization, and efficient motion planning using a moving-window RRT algorithm. With over 80 total citations, Ye’s work has significantly advanced the precision and adaptability of industrial robots in manufacturing. His notable achievements include integrating data-based cascade control for permanent magnet synchronous motors, directly improving actuator performance. Ye’s contributions are essential for students and researchers seeking to understand modern, model-free approaches to robotic control and automation.
Research Focus
Key Achievements
Top Papers
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