Micro air vehicle soaring in urban environments

Abstract

Micro-air vehicles (MAVs) are envisaged to spend a large portion of their mission within urban environments, which in general are rich in large obstacles (both natural and man-made). These obstacles can be a hindrance to MAV flight, but also have the potential to generate orographic updrafts when wind impinges on them. In theory, MAVs can exploit these updrafts in order to conserve power. However, finding, navigating between, and utilizing these updrafts is a significant challenge. We explore three aspects of this urban soaring challenge: updraft prediction and sensing, path-planning, and control. In an effort to predict urban updrafts, large-scale computational fluid dynamics (CFD) simulations of various environments have been performed. These are then combined with real-time flow field data from several multi-hole pressure probes attached to the MAV to produce better estimates of the current updraft field. The CFD results are used in large-scale path-planning through the use of a randomized planning algorithm to plan energy-efficient paths through known environments. Finally, a demonstration of “wind-hovering” in an orographic updraft using a simplified trajectory determination algorithm and control system is presented. Our vision is an autonomous platform that utilizes a database of flows around canonical shapes, together with a map, and feedback from flow sensors, to effectively navigate between urban soaring locations and maintain prolonged soaring flight.