Papers
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Total Citations
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H-Index
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About
Fan Yi is a researcher advancing the field of robotic arm path planning, with a focus on improving the efficiency and smoothness of motion algorithms. Their key research area centers on optimizing sampling-based planning methods, particularly the Rapidly-exploring Random Tree (RRT) algorithm. Yi’s most notable contribution is the development of the DAPF-RRT algorithm, which integrates dynamic step size adjustment with artificial potential field guidance to address critical limitations in the widely used RRT-Connect approach. This work tackles persistent challenges such as long search times, erratic node growth, and excessive, unsmooth path turns. By combining these techniques, Yi’s algorithm enhances both the speed and quality of computed trajectories, making robotic arm operations more practical for real-world applications. While their 2025 paper has garnered initial citations, the innovative hybrid methodology signals a promising direction for future research in autonomous manipulation. Yi’s work is particularly relevant for students and researchers in robotics, automation, and motion planning, offering a tangible improvement over traditional methods and laying groundwork for more adaptive, efficient robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Research on path planning of robotic arms based on DAPF-RRT algorithm1 citations · 2025