Mingfeng Yu
Papers
2
Total Citations
5
H-Index
2
About
Mingfeng Yu is a robotics researcher whose work focuses on intelligent motion planning and robust control for complex robotic systems operating in demanding environments. His primary research areas include path planning in cluttered spaces and adaptive control for heavy-duty manipulators. Yu’s major contribution is the development of the Multi-Indicator Heuristic Evaluation-Based Rapidly Exploring Random Tree (MIHE-RRT) algorithm, which integrates Hammersley sequence sampling with a dual optimization framework to dramatically improve path quality and search efficiency in complex environments. This work has already garnered 3 citations since its 2025 publication, signaling its immediate relevance. In a complementary vein, Yu has tackled the critical challenge of end-effector stability in long-arm, heavy-load robots. His 2023 study on adaptive buffeting sliding mode control directly addresses the low precision and unstable operation inherent in these systems, offering a dynamics-based solution that enhances both flexibility and control accuracy. By bridging theoretical algorithm design with practical industrial robotics, Yu is establishing himself as a key contributor to safer, more reliable autonomous systems in unstructured settings.
Research Focus
Key Achievements
Top Papers
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- 2