Max Robotics — Global Service Robot Directory + US Certification

About

I. Kagan Erunsal is a robotics and control systems researcher whose work focuses on autonomous multi-robot coordination, with a particular emphasis on Micro Aerial Vehicle (MAV) formations and advanced control methodologies. His research sits at the intersection of nonlinear model predictive control (NMPC), decentralized estimation, and multi-agent systems, addressing real-world challenges in cooperative aerial robotics such as search and rescue, surveillance, and scientific exploration. Erunsal's most significant contributions center on developing decentralized NMPC frameworks that enable swarms of multirotor MAVs to maintain precise 3D formations using only relative sensing and local coordinate information — a practically important approach that reduces reliance on global infrastructure like GPS. His most cited work (2019, 10 citations) pioneered decentralized nonlinear control strategies with onboard relative sensing, while subsequent research extended these ideas into tightly-coupled distributed estimation and predictive control architectures. His 2021 experimental paper demonstrated real-world viability of these algorithms, bridging the gap between theory and physical implementation. With a growing body of work spanning from algorithmic design to hardware validation, Erunsal represents an emerging voice in autonomous aerial robotics, contributing foundational tools for the next generation of intelligent, cooperative drone systems.