Papers
2
Total Citations
41
H-Index
2
About
Zijing Ye is a rising researcher in the field of mobile robotics and swarm intelligence, with a primary focus on path planning optimization. Their work centers on enhancing the efficiency and practicality of Ant Colony Optimization (ACO) algorithms for real-world robotic navigation. Ye’s major contribution lies in developing novel ACO variants that overcome fundamental limitations of the basic algorithm—namely, slow convergence, poor path smoothness, and high computational cost. Their 2023 paper introduced an angle-guided heuristic function that significantly improves search directionality, while their most-cited 2024 work, with 38 citations, further advanced the field by integrating farthest point optimization and multi-objective strategies into the ACO framework. This combined approach enables robots to plan more efficient, smoother, and computationally lighter paths in complex environments. Though early in their career, Ye’s work has already garnered attention, demonstrating clear impact in addressing practical challenges of autonomous navigation. Their research is particularly valuable for students and engineers working on real-time path planning in dynamic or obstacle-rich settings, offering scalable solutions that balance multiple performance criteria.
Research Focus
Key Achievements
Top Papers
- 1
- 2