Sense and Avoid in UAS: Research and Applications

There is increasing interest in the potential of UAV (Unmanned Aerial Vehicle) and MAV (Micro Air Vehicle) technology and their wide ranging applications including defense missions, reconnaissance and surveillance, border patrol, disaster zone assessment and atmospheric research. High investment levels from the military sector globally is driving research and development and increasing the viability of autonomous platforms as replacements for the remotely piloted vehicles more commonly in use.

UAV/UAS pose a number of new challenges, with the autonomy and in particular collision avoidance, detect and avoid, or sense and avoid, as the most challenging one, involving both regulatory and technical issues.

Sense and Avoid in UAS: Research and Applications covers the problem of detect, sense and avoid in UAS (Unmanned Aircraft Systems) in depth and combines the theoretical and application results by leading academics and researchers from industry and academia.

Key features:

• Presents a holistic view of the sense and avoid problem in the wider application of autonomous systems
• Includes information on human factors, regulatory issues and navigation, control, aerodynamics and physics aspects of the sense and avoid problem in UAS
• Provides professional, scientific and reliable content that is easy to understand
• Includes contributions from leading engineers and researchers in the field

Sense and Avoid in UAS: Research and Applications is an invaluable source of original and specialised information. It acts as a reference manual for practising engineers and advanced theoretical researchers and also forms a useful resource for younger engineers and postgraduate students. With its credible sources and thorough review process, Sense and Avoid in UAS: Research and Applications provides a reliable source of information in an area that is fast expanding but scarcely covered.

About the Editor

Plamen Angelov is a Reader in Computational Intelligence and coordinator of the Intelligent Systems Research at Infolab21, Lancaster University, UK. He is a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE) and Chair of two Technical Committees (TC): the TC on Standards, Computational Intelligence Society and the TC on Evolving Intelligent Systems, Systems, Man and Cybernetics Society. He is also a member of the UK Autonomous Systems National TC, of the Autonomous Systems Study Group, NorthWest Science Council, UK and of the Autonomous Systems Network of the Society of British Aerospace Companies. He is a very active academic and researcher who has authored or co-authored over 150 peer-reviewed publications in leading journals, 50+ peer-reviewed conference proceedings, a patent, a research monograph, a number of edited books, and has an active research portfolio in the area of computational intelligence and autonomous system modelling, identification and machine learning. He has internationally recognised pioneering results in online and evolving methodologies and algorithms for knowledge extraction in the form of human-intelligible fuzzy rule-based systems and autonomous machine learning. Angelov is also a very active researcher leading projects funded by EPSRC, ASHRAE-USA, EC FP6 and 7, The Royal Society, Nuffield Foundation, DTI/DBIS, MoD and other industry players (BAE Systems, 4S Information Systems, Sagem/SAFRAN, United Aircraft Corporation and Concern Avionica, NLR, etc.).

His research contributes to the competitiveness of the industry, defence and quality of life through projects such as ASTRAEA – a £32M (phase I and £30M phase II) programme, in which Angelov led projects on collision avoidance (£150K, 2006/08) and adaptive routeing (£75K, 2006/08). The work on this project was recognised by The Engineer Innovation and Technology 2008 Award in two categories: (i) Aerospace and Defence and (ii) The Special Award. Other examples of research that has direct impact on the competitiveness of UK industry and quality of life are the BAE Systems-funded project on sense and avoid (principal investigator, £66K, 2006/07), BAE-funded project on UAS passive sense, detect and avoid algorithm development (£24K consultancy, a part of ASTRAEA-II, 2009), BAE Systems-funded project (co-investigator, £44K, 2008) on UAV safety support, EC-funded project (₠1.3M, co-investigator) on safety (and maintenance) improvement through automated flight data analysis, Ministry of Defence-funded projects (‘Multi-source Intelligence: STAKE: Real-time Spatio-Temporal Analysis and Knowledge Extraction through Evolving Clustering’, £30K, principal investigator, 2011 and ‘Assisted Carriage: Intelligent Leader–Follower Algorithms for Ground Platforms’, £42K, 2009 which developed an unmanned ground-based vehicle prototype taken further by Boeing-UK in a demonstrator programme in 2009–11), the £9M project GAMMA: Growing Autonomous systems Mission Management, 2011–2014, in which PI of £480K work); funded by the Regional Growth Fund, UK Government; the £3M project CAST (Coordinated Airborne Studies in the Tropics) which envisages usage of the Global Hawk with NASA so-called ‘innovation vouchers’ by the North-West Development Agency-UK and Autonomous Vehicles International Ltd (£10K, 2010, principal investigator), MBDA-led project on algorithms for automatic feature extraction and object classification from aerial images (£56K, 2010) funded by the French and British defence ministries. Angelov is also the founding Editor-in-Chief of Springer's journal Evolving Systems, and serves as an Associate Editor of several other international journals. He chairs annual conferences organised by the IEEE, acts as Visiting Professor (2005, Brazil; 2007, Germany; 2010, Spain) and regularly gives invited and plenary talks at leading companies (Ford, Dow Chemical USA, QinetiQ, BAE Systems, Thales, etc.) and universities (Michigan, USA; Delft, the Netherlands; Leuven, Belgium; Linz, Austria; Campinas, Brazil; Wolfenbuettel, Germany; etc.).