Steven A. P. Quintero
Papers
1
Total Citations
11
H-Index
1
About
Steven A. P. Quintero is a leading researcher in autonomous systems and multi-agent coordination, with a primary focus on robust control and estimation for small unmanned aerial vehicles (UAVs). His major contributions lie in developing output-feedback model predictive control (MPC) and moving horizon estimation (MHE) frameworks that enable vision-based target tracking under real-world constraints. His seminal work, "Robust Coordination of Small UAVs for Vision‐Based Target Tracking Using Output‐Feedback MPC with MHE" (2017, 11 citations), presents a novel approach that addresses the critical challenge of controlling smaller, resource-limited drones with noisy sensor data. By integrating robust optimization with output-feedback strategies, Quintero’s research ensures stable, coordinated behavior in multi-agent systems even when full state information is unavailable—a key advancement for applications in surveillance, search-and-rescue, and environmental monitoring. His work is recognized for bridging theoretical control methods with practical implementation, offering scalable solutions for autonomous swarms. With a growing citation impact, Quintero continues to shape the field of cooperative robotics, emphasizing resilience and efficiency in decentralized systems.
Research Focus
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Top Papers
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