Cong Khanh Dinh
Papers
1
Total Citations
3
H-Index
1
About
Cong Khanh Dinh is a researcher advancing the frontiers of multi-agent robotics and real-time motion planning. His work centers on developing computationally efficient, optimization-based control strategies for swarms of autonomous agents, with a particular focus on distributed Model Predictive Control (DMPC). His most cited paper, "Online B-Spline Based Trajectory Planning for Swarm of Agents Using Distributed Model Predictive Control" (2024), introduces a novel framework that leverages B-spline parameterization to reduce the computational burden of DMPC while maintaining robust constraint enforcement and dynamic stability. This approach enables scalable, real-time trajectory generation for large robot teams, addressing a critical bottleneck in swarm robotics. Although early in his career, with this work already garnering 3 citations, Dinh is establishing a reputation for tackling the trade-off between computational tractability and control performance. His contributions are particularly relevant for applications in automated warehouses, environmental monitoring, and coordinated drone operations, where efficient, decentralized decision-making is essential. Dinh’s research promises to make swarm intelligence more practical and deployable in real-world scenarios.
Research Focus
Key Achievements
Top Papers
- 1