Bird Velocity Optimization as Inspiration for Unmanned Aerial Vehicles in Urban Environments

Abstract

Small unmanned aerial vehicles (SUAVs) operating in urban environments must deal with complex wind flows and endurance limitations caused by current battery technology. Birds offer inspiration regarding how to fly in these environments and how to exploit complex wind flows as an energy source. On a broad scale, migrating birds adjust airspeed to minimize cost of transport (COT) in response to wind conditions, but it is unknown whether birds implement these strategies in fine-scale, complex environments. GPS backpacks were used to track 11 urban nesting gulls and found they soared extensively during daily commutes, using thermal and orographic updrafts. This paper outlines COT theory and proposes a model for optimizing airspeed for wind while maintaining flight trajectory. The gull flight paths were tested for COT adjustments, considering their flapping and soaring strategies, and it was found that the birds were able to make energy savings of 31% based on having a best glide speed when soaring that was similar to their minimum power speed when flapping. These models calculated optimum airspeeds based on wind speed and direction and could be implemented on SUAV platforms with wind sensing capabilities. This approach could significantly reduce energy requirements for SUAVs flying in urban environments.