Bird-inspired Velocity Optimization for Unmanned Aerial Vehicles in the Urban Environment

Small Unmanned Aerial Vehicles, SUAVs, are low-cost quick to launch platforms which offer potential for a range of roles in urban environments. However, these environments create complex wind flows that present control issues for small, low speed platforms. Further to this, battery technology does not yet offer the power-weight capacity to enable the endurance requirements for such missions. In comparison, birds of comparable size and weight are not only able to manage complex wind flow, but also exploit the environment as a locomotive energy source. Birds in migration are known to adjust airspeed to minimize the energetic cost of transport in response to wind conditions however, it is unknown whether birds implement the same velocity optimization strategies in more complex environments and while performing energy harvesting flight strategies. This study used Global Positioning System (GPS) backpacks to track 11 urban nesting gulls and found that during 193 daily commutes the gulls were able to soar 44% of the time by making use of both thermal and orographic updrafts. We outline cost of transport (CoT) theory and propose a model for optimizing airspeed for given wind conditions whilst maintaining a trajectory to a given location. We used the gull flight paths to test for CoT velocity adjustments by considering their flapping and soaring strategies. We found that by having a similar best glide speed and minimum power speed in soaring and flapping flight the gulls were able to make energy savings of as much as 30%. These models calculated optimum ground and airspeeds for known wind conditions assuming trajectory holding throughout flight, and as such could be implemented on a SUAV platform with wind sensing capabilities. This approach could significantly reduce the energy requirements for a SUAV navigating in an urban environment.