Sean Humbert

University of Colorado Boulder, University of Maryland, College Park, University of Colorado System

Papers

Total Citations

H-Index

About

Sean Humbert is a leading researcher in autonomous robotics, with key contributions spanning swarm intelligence, decentralized control, and bio-inspired aerial systems. His most impactful work, "Scalable Event-Triggered Data Fusion for Autonomous Cooperative Swarm Localization" (2019, 12 citations), introduces a Kalman filter-based method that enables large networks of autonomous robots to perform cooperative localization without overwhelming computational demands—a critical breakthrough for scaling swarm operations. Humbert also advanced the understanding of non-holonomic systems through "Formation Control of Non-Holonomic Mobile Robots Moving on Slippery Surfaces" (2020, 2 citations), where he experimentally modeled the uncertainties of robots on gravel, demonstrating that deterministic models fail in real-world conditions. Earlier, his work on "Identification of a Robotic Samara Aerodynamic/Multi-Body Dynamic Model" (2010, 4 citations) explored bio-inspired flight, modeling the unique autorotative descent of samara seeds for robotic applications. While his citation counts reflect a focused, emerging impact, Humbert’s research is notable for bridging theoretical control with practical, scalable solutions for multi-robot systems, making him a key figure in the future of autonomous swarms.