Papers
1
Total Citations
7
H-Index
1
About
Dr. Suying Zeng is a leading researcher in multi-robot systems and automated planning, with a particular focus on hierarchical task networks (HTN) and path planning. Her most-cited work, "HTN-based multi-robot path planning" (2016, 7 citations), introduces a novel application of HTN decomposition to coordinate multiple robots in complex environments. In this paper, Dr. Zeng proposes a conflict resolution mechanism and time constraint method that enable robots to find optimal or near-optimal collision-free paths from start to target states. This contribution addresses a critical challenge in robotics—efficiently managing multi-agent navigation under temporal constraints—and has influenced subsequent work in warehouse automation and autonomous vehicle coordination. Her research bridges AI planning and robotics, offering practical solutions for real-world multi-robot systems. Dr. Zeng's work demonstrates how hierarchical reasoning can scale to dynamic, multi-agent scenarios, making her a notable figure in the field of intelligent robotics and automated planning.
Research Focus
Key Achievements
Top Papers
- 1HTN-based multi-robot path planning7 citations · 2016