AIRL is led by Prof. Suresh Sundaram.

The lab focuses on a range of problems related to the guidance, navigation, design, and control of Unmanned Aerial Vehicles (UAVs), Unmanned Ground Vehicles (UGVs), and Under Water Vehicles (UWVs) using modern control theory. The lab explores the theoretical and practical aspects of reinforcement learning and deep learning like spiking neural networks, continual learning, and complex-valued deep learning. It also focuses on developing practical solutions for applications in computer vision, satellite imaging, pursuit-evasion games, and motion planning. There is a dedicated team that focuses on building and testing hexacopters and quadcopters; primarily focused on variable pitch propulsion and morphable drones for easy traversal through obstacles. Other areas our members work on include smart community power grids for efficient distribution and consumption of power.