Papers
5
Total Citations
102
H-Index
4
About
Zhijun Wu is a leading researcher in robotics and intelligent systems, with a primary focus on trajectory planning and optimization for industrial manipulators. His major contributions lie in developing novel algorithms that simultaneously minimize execution time and joint vibration—critical for enhancing productivity in pick-and-place operations. Wu pioneered the "Time-Jerk optimal Trajectory Planning" methodology using a hybrid Whale Optimization Algorithm and Genetic Algorithm (WOA-GA), which has garnered 43 citations for its impact on reducing operational time and mechanical stress. He also introduced a locally asymmetrical jerk motion profile for point-to-point trajectory planning (30 citations), significantly improving motion efficiency. His work extends to multi-point trajectory generation using series-parallel analytical strategies, and he has recently ventured into agricultural robotics with YOLOC-tiny, a lightweight real-time detection model for multi-ripeness citrus fruits in unstructured environments (12 citations). Wu’s multi-objective optimization framework, CMOSPBO, further advances smooth, feasible trajectories for manufacturing. With over 100 citations across his most-cited works, Wu is recognized for bridging theoretical optimization with practical robotic applications, making him a key figure in modern industrial automation.
Research Focus
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Top Papers
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