Bird-Inspired Gust Soaring for Unmanned Air Vehicles

The range and endurance of small unmanned aerial vehicles (SUAVs) is currently hindered by their limited battery capacity. Many SUAVs have a maximum flight time of up to ninety minutes, severely restricting their utility and preventing their benefits from being realised in fields such as disaster response, remote sensing (e.g. for agriculture and environmental monitoring) and reconnaissance. By performing particular manoeuvres to interact with local airflow appropriately, these vehicles can increase their potential or air-relative kinetic energy (the energy available to do useful work [1]), enabling them to fly further and for longer; this energy gain flight is known as 'soaring'. Updrafts of air form one condition for soaring flight (known as 'static soaring'); a bird can gain a 'free ride' to higher altitudes by flying in a thermal, for example, increasing its potential energy. Energy can also be extracted in nonuniform wind fields, where the wind direction and strength change in space and time, by utilising wind gradients - a technique known as 'gradient soaring'. Albatross are famous for exploiting this technique within the strong wind gradients above the ocean (in the atmospheric boundary layer) to achieve long-distance low-energy-expenditure travel. Automatic control systems for exploiting updrafts and large-scale gradients have received significant research, however these energy sources are not applicable for vehicles unable to deviate substantially from their desired flight path to exploit them, due for example to noise abatement procedures or a requirement to keep out of sight. Birds can be observed to gain energy en route through appropriate reactions to stochastic gradients - small-scale spatial gradients, caused for example by buildings, and gusts (gradients in time). This is known as 'gust soaring'. The goal of this research is to develop new gust soaring control algorithms for SUAVs in order to extend their range and endurance. The research will particularly focus on urban environments, where small-scale spatial gradients are common due to the complex interactions between the wind and structures.

FARSCOPE-TU will deliver a step change in UK capabilities in robotics and autonomous systems (RAS) by elevating technologies from niche to ubiquity. It meets the critical need for advanced RAS, placing the UK in prime position to capture a significant proportion of the estimated $18bn global market in advanced service robotics. FARSCOPE-TU will provide an advanced training network in RAS, pump priming a generation of professional and adaptable engineers and leaders who can integrate fundamental and applied innovation, thereby making impact across all the "four nations" in EPSRC's Delivery Plan. Specifically, it will have significant immediate and ongoing impact in the following six areas:
1. Training: The FARSCOPE-TU coherent strategy will deliver five cohorts trained in state-of-the-art RAS research, enterprise, responsible innovation and communication. Our students will be trained with wide knowledge of all robotics, and deep specialist skills in core domains, all within the context of the 'innovation pipeline', meeting the need for 'can-do' research engineers, unafraid to tackle new and emergent technical challenges. Students will graduate as future thought leaders, ready for deployment across UK research and industrial innovation.
2. Partner and industrial impact: The FARSCOPE-TU programme has been designed in collaboration with our industrial and end-user partners, including: DSTL; Thales; Atkins; Toshiba; Roke Manor Research; Network Rail; BT; National Nuclear Lab; AECOM; RNTNE Hospital; Designability; Bristol Heart Inst.; FiveAI; Ordnance Survey; TVS; Shadow Robot Co.; React AI; RACE (part of UKAEA) and Aimsun. Partners will deliver context and application-oriented training direct to the students throughout the course, ensuring graduates are perfectly placed to transition into their businesses and deliver rapid impact.
3. RAS community: FARSCOPE-TU will act as multidisciplinary centre in robotics and autonomous systems for the whole RAS community, provide an inclusive model for future research and training centres and bring new opportunities for networking between other centres. These include joint annual conference with other RAS CDTs and training exchanges. FARSCOPE-TU will generate significant international exposure within and beyond the RAS community, including major robotics events such as ICRA and IROS, and will interface directly with the UK-RAS network.
4. Societal Impact: FARSCOPE-TU will promote an informed debate on the adoption of autonomous robotics in society, cutting through hype and fear while promoting the highest levels of ethics and safety. All students will design and deliver public engagement events to schools and the public, generating knock-on impact in two ways: greater STEM uptake enhances future economic potential, and greater awareness makes people better users of robots, amplifying societal benefits.
5. Economic impact: FARSCOPE-TU will not only train cohorts in fundamental and applied research but will also demonstrate how to bridge the "technology valley of death" between lower and higher TRL. This will enable students to exploit their ideas in technology incubators (incl. BRL incubator, SetSquared and EngineShed) and through IP protection. FARSCOPE-TU's vision of ubiquitous robotics will extend its impact across all UK industrial and social sectors, from energy suppliers, transport and agriculture to healthcare, aging and human-machine interaction. It will pump-prime ubiquitous UK robotics, inspiring and enabling myriad new businesses and economic and social impact opportunities.
6. Long-term Impact: FARSCOPE-TU will have long-term impact beyond the funded lifetime of the Centre through a network for alumni, enabling knowledge exchange and networking between current and past students, and with partners and research groups. FARSCOPE-TU will have significant positive impact on the 80-strong non-CDT postgraduate student body in BRL, extending best-practice in supervision and training.