Mitchell Cohen

Papers

Total Citations

H-Index

About

Mitchell Cohen is a leading researcher in autonomous aerial robotics, with a primary focus on state estimation and control for unconventional vertical takeoff and landing (VTOL) UAVs. His most impactful work, "Navigation and Control of Unconventional VTOL UAVs in Forward-Flight With Explicit Wind Velocity Estimation" (2020, 17 citations), introduces a tightly-coupled state estimation approach that simultaneously estimates aircraft navigation states, sensor biases, and wind velocity—enabling robust forward-flight control without dedicated airspeed sensors. This contribution directly addresses a critical challenge in transitioning VTOL aircraft between hover and cruise modes. Cohen also developed **navlie** (2023), an open-source Python package for state estimation on Lie groups, which provides researchers with a modular prototyping framework for testing navigation algorithms on manifolds. By bridging theoretical Lie group methods with practical implementation, navlie accelerates development cycles for estimation tasks in robotics. Cohen’s work is distinguished by its dual impact: advancing fundamental estimation theory while delivering deployable solutions for next-generation UAVs. His research is essential reading for engineers working at the intersection of nonlinear control, sensor fusion, and autonomous flight in challenging aerodynamic environments.