Xue-Lei Jing
Papers
1
Total Citations
9
H-Index
1
About
Xue-Lei Jing is a pioneering researcher in agricultural robotics and intelligent optimization, whose work bridges the gap between computational intelligence and precision farming. His most impactful contribution, "An effective knowledge-based evolutionary algorithm for task assignment problem of pollination robots and spraying drones in multi-orchard scenarios" (2025, 9 citations), introduces a novel algorithmic framework that optimizes the coordination of heterogeneous robotic systems in complex agricultural environments. By integrating domain-specific knowledge into evolutionary computation, Jing addresses critical challenges in task allocation for pollination robots and spraying drones, enabling efficient, scalable operations across multiple orchard layouts. This work has immediate implications for sustainable agriculture, reducing resource waste and enhancing crop yield through smart automation. With a growing citation footprint, Jing’s research is gaining traction among scholars in robotics, operations research, and agritech. His approach exemplifies how evolutionary algorithms can be tailored to real-world constraints, offering a blueprint for future studies in multi-agent systems and environmental monitoring. Jing’s contributions position him as a rising voice in the intersection of artificial intelligence and agricultural engineering.
Research Focus
Key Achievements
Top Papers
- 1