Report
Teaser, summary, work performed and final results
Periodic Reporting for period 2 - BIAF (Bird Inspired Autonomous Flight)
Teaser
The agile and efficient flight of birds shows what flight performance is physically possible, and in theory could be achieved by unmanned air vehicles (UAVs) of the same size. The overall aim of this project is to enhance the performance of small scale UAVs by developing novel...
Summary
The agile and efficient flight of birds shows what flight performance is physically possible, and in theory could be achieved by unmanned air vehicles (UAVs) of the same size. The overall aim of this project is to enhance the performance of small scale UAVs by developing novel technologies inspired by understanding how birds are adapted to interact with airflows. Small UAVs have the potential to dramatically change current practices in many areas such as, search and rescue, surveillance, and environmental monitoring. Currently the utility of these systems is limited by their operational endurance and their inability to operate in strong turbulent winds, especially those that often occur in urban environments. Birds are adapted to be able to fly in these conditions and actually use them to their advantage to minimise their energy output.
This project is composed of three tracks which contain elements of technology development, as well as scientific investigation looking at bird flight behaviour and aerodynamics. The first track looks at developing path planning algorithms for UAVs in urban environments based on how birds fly in these areas, by using GPS tracking and computational fluid dynamics alongside trajectory optimization. The second track aims to develop artificial wings with improved gust tolerance inspired by the features of feathered wings. Here, high speed video measurements of birds flying through gusts will be used alongside wind tunnel testing of artificial wings to discover what features of a bird’s wing help to alleviate gusts. The third track develops novel force and flow sensor arrays for autonomous flight control based on the sensor arrays found in flying animals. These arrays will be used to make UAVs with increased agility and robustness. This unique bird inspired approach uses biology to show what is possible, and engineering to find the features that enable this performance and develop them into functional technologies.
Work performed
In the first track, 11 lesser black backed gulls have been tagged with GPS backpacks and their flight paths successfully recorded for three breeding seasons so far. Computer models of the wind flows encountered by the birds have also been developed. This is the first high resolution dataset of its kind, measuring bird flight behaviour in an urban environment and shows that the birds perform a range of energy saving behaviours such as thermalling, and using orographic lift, and that they adjust their flight patterns to suit local weather conditions in a highly efficient manner.
Measurements of the wing shapes of birds of prey as they respond to controlled gusts has been completed in track two. A series of three experiments were conducted testing different gust conditions and the wing shapes of the birds were then successfully measured based on high-speed video. A clear gust alleviation mechanism was identified and is currently being analysed based on high-resolution 3D surface reconstructions that resolve the shape of the wing down to the millimetre level.
A series of distributed force and flow sensing systems for a small-scale fixed wing unmanned air vehicle (UAV) have been developed and characterised in the wind tunnel for track three. Each iteration has incorporated more sensor channels and higher sampling rates. Progress has been made on developing an advanced reflexive flight control system for closed loop flight control based on machine learning techniques.
Final results
The dataset collected from the urban gulls combines information about their location, behaviour, flight strategy, habitat use, and weather conditions at a very high spatial and temporal resolution. This is the first dataset of its kind for birds living in an urban environment and is revealing many interesting aspects of the flight strategies they use. The birds appear to make significant energy savings during their flights across the city and we are currently developing path planning algorithms based on these strategies with future application to unmanned vehicle operations in urban environments.
When encountering a controlled wind gust we measured a distinct strategy for gust rejection used by birds of prey. This strategy has not been identified before and we are currently developing models to investigate the dynamics that allows the birds to deal so effectively with wind gusts. Through understanding the strategy used by birds we are starting to develop wings for unmanned air vehicles which use the same principle with the aim to improve the gust rejection abilities of these vehicles.
We have developed a distributed force and flow sensor system for UAVs which allows us to measure in real-time the force and flows acting on the wing at a level of detail that have not been possible before. This sensor information is allowing us to develop a flight control system which uses machine learning techniques to learn how the wing responses to disturbances and to take advantage of this information to develop flight control systems with increased agility and robustness.