16 April/May 2024 | Uncrewed Systems Technology Dr Donough Wilson Dr Wilson is innovation lead at aviation, defence, and homeland security innovation consultants, VIVID/ futureVision. His defence innovations include the cockpit vision system that protects military aircrew from asymmetric high-energy laser attack. He was first to propose the automatic tracking and satellite download of airliner black box and cockpit voice recorder data in the event of an airliner’s unplanned excursion from its assigned flight level or track. For his ‘outstanding and practical contribution to the safer operation of aircraft’ he was awarded The Sir James Martin Award 2018/19, by the Honourable Company of Air Pilots. Paul Weighell Paul has been involved with electronics, computer design and programming since 1966. He has worked in the realtime and failsafe data acquisition and automation industry using mainframes, minis, micros and cloud-based hardware on applications as diverse as defence, Siberian gas pipeline control, UK nuclear power, robotics, the Thames Barrier, Formula One and automated financial trading systems. Ian Williams-Wynn Ian has been involved with uncrewed and autonomous systems for more than 20 years. He started his career in the military, working with early prototype uncrewed systems and exploiting imagery from a range of systems from global suppliers. He has also been involved in ground-breaking research including novel power and propulsion systems, sensor technologies, communications, avionics and physical platforms. His experience covers a broad spectrum of domains from space, air, maritime and ground, and in both defence and civil applications including, more recently, connected autonomous cars. Professor James Scanlan Professor Scanlan is the director of the Strategic Research Centre in Autonomous Systems at the University of Southampton, in the UK. He also co-directs the Rolls-Royce University Technical Centre in design at Southampton. He has an interest in design research, and in particular how complex systems (especially aerospace systems) can be optimised. More recently, he established a group at Southampton that undertakes research into uncrewed aircraft systems. He produced the world’s first ‘printed aircraft’, the SULSA, which was flown by the Royal Navy in the Antarctic in 2016. He also led the team that developed the ULTRA platform, the largest UK commercial UAV, which has flown BVLOS extensively in the UK. He is a qualified full-size aircraft pilot and also has UAV flight qualifications. Dr David Barrett Dr David Barrett’s career includes senior positions with companies such as iRobot and Walt Disney Imagineering. He has also held posts with research institutions including the Charles Stark Draper Laboratory, MIT and Olin College, where he is now Professor of Mechanical Engineering and Robotics, and Principal Investigator for the Olin Intelligent Vehicle Laboratory. He also serves in an advisory capacity on the boards of several robotics companies. Uncrewed Systems Technology’s consultants Researchers in China are finding ways around the limitations of UAV battery life for large-scale monitoring applications (writes Nick Flaherty). As missions cannot be completed by a single UAV powered by one battery (typically lasting 30-40 minutes), owing to the wide scope of inspections required on a construction project, the scheduling of UAVs of multiple types and their charging demands are key considerations. Construction environments vary dynamically, so multi-round inspection tasks must be conducted to search for hidden dangers. To prevent collisions between UAVs and facilities, no-fly zones are needed to limit the routes that UAVs can use when travelling between sites, making path-planning challenging. The classical vehicle routing (VRP) algos used for logistics and delivery services do not work for large monitoring applications, say researchers at Shanghai University in China, who are developing alternatives. In conventional VRP scenarios, UAVs usually visit each customer point once within a known time window, with no instances of network inaccessibility between customer points. However, construction monitoring needs UAVs to make multiple visits to specific points within periodic time windows with nofly zones, and consider the charging locations. A mathematical model and a tailored algo were developed for planning UAV inspection routes to search for hidden dangers on an engineering project. Consecutive inspection tasks for a given site are separated by a time window, and a mixed-integer linear programming (MILP) model is used to consider the limitations of the batteries and no-fly zones. This model determines the routing and scheduling of multiple different UAVs with varying periodic inspection and charging cycles and no-fly-zone constraints. A tailored algo, based on a variable neighbourhood search (VNS), was used to solve the model at large scale. This is being used for inspection at the Shiziyang Bridge project in Guangdong province, which is being built with a world-record main span of 2180 m. Batteries Finding the optimum route for large-scale UAV inspections
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