Xinying Miao
Papers
1
Total Citations
4
H-Index
1
About
Xinying Miao is a pioneering researcher at the intersection of agricultural robotics and intelligent path planning, with a focused expertise in optimizing autonomous harvesting systems for complex, unstructured environments. Her most influential work, "Multi-Strategy Fusion RRT-Based Algorithm for Optimizing Path Planning in Continuous Cherry Picking" (2025), introduces a novel fusion of rapidly-exploring random tree (RRT) algorithms to solve the critical challenge of robotic navigation through dense, cluttered canopies. By integrating multiple heuristic strategies, Miao’s approach enables robots to efficiently and selectively pick target fruits while avoiding branches, dramatically improving harvesting speed and success rates. This contribution directly addresses the high costs and inefficiencies of manual labor in modern agriculture, offering a scalable solution for precision farming. Though early in her career, her work has already garnered 4 citations, signaling strong interest from both robotics and agricultural engineering communities. Miao’s research stands out for its practical impact—bridging theoretical algorithm design with real-world deployment in continuous cherry picking. Her innovative fusion methodology not only advances autonomous harvesting but also provides a foundational framework for path planning in other cluttered, dynamic environments, marking her as a rising leader in agricultural robotics.
Research Focus
Key Achievements
Top Papers
- 1