Yufei ZHOU
Papers
1
Total Citations
3
H-Index
1
About
Yufei Zhou is a researcher in robotics and optimization, with a focus on trajectory planning and obstacle avoidance for redundant robotic manipulators. Their most notable contribution is a 2023 study that unifies trajectory tracking and obstacle avoidance into a single optimization problem, solved using an improved grey wolf optimizer. This work introduces a bounding-box-based obstacle space model and employs the GJK algorithm to compute minimum distances between the manipulator and obstacles, enabling efficient and safe motion planning. With 3 citations, this paper demonstrates early impact in the field of intelligent robotic control. Zhou’s approach stands out for its integration of swarm intelligence with real-time robotic constraints, offering a novel solution to the challenge of redundant manipulator navigation in cluttered environments. Their work is particularly relevant for researchers in industrial automation, autonomous systems, and optimization-driven robotics, providing a foundation for further advances in collision-free motion planning.
Research Focus
Key Achievements
Top Papers
- 1