Xuecheng Chen
Papers
2
Total Citations
12
H-Index
2
About
Xuecheng Chen is a rising researcher at the intersection of multi-agent systems and autonomous navigation, with key contributions in pedestrian behavior modeling and robotic coordination. His work on "The Group Interaction Field for Learning and Explaining Pedestrian Anticipation" (2023, 10 citations) addresses a critical gap in unmanned systems—enabling service robots and self-driving cars to intuitively predict human movements in dense crowds, much like humans do. This research provides an interpretable framework for anticipating pedestrian actions, a foundational step toward safer human-robot interaction. Chen also tackles high-stakes multi-robot coordination with "FireHunter: Toward Proactive and Adaptive Wildfire Suppression via Multi-UAV Collaborative Scheduling" (2024, 2 citations), which introduces a novel scheduling system for unmanned aerial vehicles to simultaneously monitor and suppress wildfires in unpredictable, cold-start environments. This work demonstrates his ability to apply multi-robot systems to complex, real-world challenges. Though early in his career, Chen’s focus on explainable AI and adaptive multi-agent coordination positions him as a promising voice in autonomous systems, with potential to shape how robots perceive and act in dynamic, human-centric spaces.
Research Focus
Key Achievements
Top Papers
- 1
- 2