Reliability and accuracy of navigation in flying drones are one of the key challenges that must be solved in autonomous applications. Accurate knowledge of position, attitude, and velocity is a critical input for drones operating in cluttered and challenging environments such as cities, forests or mountain terrain. The possibility of (Global Navigation Satellite System) GNSS failure due to signal obstruction or external interference can cause complete failure of a drone navigation system which would be unacceptable for any future beyond visual line of site commercial applications.

Currently, at TOPO a novel navigation system being developed based on the flight dynamics. Drones can navigate through a complex environment even with the absence of GNSS signal. A key challenge for this novel navigation system to operate accurately however is dealing with wind and gust effects. Wind gust can drift a drone and cause 10’s to 100 eds of meters accumulated navigation errors in the autopilot.

This current research project aims at drawing inspiration from nature in solving this problem. Development of novel sensor network and analysis framework (based on Computational Fluid Dynamics CFD and Deep Neural Networks) will be aiming to achieve real-time drone ‘skin’ sensation of the wind effects.

For further info, see the TOPO lab website.