Huangke Chen

National University of Defense Technology

Papers

Total Citations

H-Index

About

Huangke Chen is a researcher whose work lies at the intersection of swarm robotics, collective intelligence, and environmental modeling. His most-cited paper, "TH-GRN Model Based Collective Tracking in Confined Environment" (2019), introduces a novel gene regulatory network (GRN) approach for enabling multi-robot systems to collaboratively track targets in constrained spaces—a critical challenge for applications like disaster response or industrial inspection. This contribution has garnered 4 citations, reflecting its niche but growing influence in the field. Chen’s research focuses on designing decentralized algorithms that allow simple agents to achieve complex, coordinated behaviors without central control, drawing inspiration from biological systems. His work on the TH-GRN model demonstrates how hybrid topological-hormonal mechanisms can enhance robustness and adaptability in dynamic environments. While still early in his career, Chen’s contributions are paving the way for more resilient and scalable swarm systems, offering practical solutions for real-world confined-space operations. His approach bridges theoretical modeling with applied robotics, making his research a valuable resource for students and engineers exploring bio-inspired collective tracking.