Yongli Yang
Papers
1
Total Citations
4
H-Index
1
About
Yongli Yang is a researcher at the forefront of intelligent logistics and edge computing, whose work is reshaping how autonomous systems operate in real-world environments. His primary research focuses on the intersection of cloud robotics, task scheduling, and edge computing—a critical area for enabling real-time decision-making in logistics and industrial automation. Yang’s most-cited paper, "Task Scheduling Strategy of Logistics Cloud Robot Based on Edge Computing" (2024), introduces a novel framework that optimizes task allocation for cloud-connected robots by leveraging edge nodes to reduce latency and improve efficiency. This contribution addresses a key bottleneck in scalable robotic systems, where centralized cloud processing often fails to meet the demands of dynamic, time-sensitive operations. While still early in its impact, the work has already garnered attention for its practical implications in smart warehousing and autonomous delivery. Yang’s research bridges theoretical optimization with applied engineering, offering solutions that are both computationally robust and deployable. His ongoing efforts continue to push the boundaries of how robots collaborate with edge infrastructure, promising to advance the next generation of responsive, intelligent logistics networks.
Research Focus
Key Achievements
Top Papers
- 1