During the past two decades, with the advancement of avionics, control systems, design, product methods, and communication systems, UAVs have gained more interest from both civil and military customers. Hence, more researchers have dedicated their time to developing new applications for drones and improving their performance. In this study, a literature review on drone applications is conducted. It is explained that they can be more effective and beneficial when merged with preexisting systems, and thus making a system of systems. Further, we have classified UAV applications more comprehensively. This classification can be very useful for providing insights when designing new UAVs. Finally, previous works are discussed thoroughly and diagrams are developed to show the research focus in this field. These statistical diagrams can also be used as a gap analysis tool.

This study presents a methodology to estimate the battery consumption of an electric powerplant, based on brushless motors, typically used in light unmanned aerial systems. The methodology models brushless motors through an equivalent circuit obtained from their dynamic behaviour. Propellers’ data are taken from an experimental database. Furthermore, a variable speed controller efficiency is considered in the methodology. All the parameters involved in the model are adjusted by minimising the mean quadratic error of measurements taken in both direct and alternating currents. This model allows designers to predict energy consumption, also if any element of the powerplant changes, such as battery or propeller. Thus, it is useful for selecting the best powerplant for an actual RPAS operation. The results obtained to predict the current consumption of several electric powerplants show a coefficient of determination higher than 0.96. Finally, the methodology is validated by means of a case study of an actual RPAS, where the best powerplant is selected in terms of endurance.

The ablation zones of debris-covered glaciers in Himalaya exhibit heterogeneous processes and melt patterns. Although sub-debris melt is measured at ablation stakes, the high variability of debris thickness necessitates distributed melt measurements at the glacier scale. Focusing on Annapurna III Glacier, we used uncrewed aerial system (UAS) photogrammetry to estimate total volume loss and slope-perpendicular glacier melt between May and November 2019 using flow-corrected point clouds. Results indicated the average elevation change was −1.10 ± 0.19 m, while the mean melt was −0.87 m w.e., equating to a mean melt rate of −0.47 cm w.e. d−1. However, the spatial pattern was highly variable due to complex local processes necessitating future study over short intervals. The evaluation of specific areas showed the interplay of debris thickness variability, subseasonal debris redistribution, supraglacial channel reconfiguration and the imprint of relict ice cliffs in leading to contemporary melt rates. Ice cliffs had higher melt distances (mean −3.9 ± 0.19 m) compared to non-cliff areas (mean −0.75 ± 0.19 m) and were the predominant control on the spatial patterns of seasonal melt rates. Crucially, the definition of ice cliff areas from thinning data has a profound impact on derived melt rates and melt enhancement. Our study demonstrates the possibility and utility of deriving fully-distributed slope-perpendicular melt measurements.

The ability to quickly fabricate small unmanned aircraft system (sUAS) through Additive Manufacturing (AM) methods opens a range of new possibilities for the design and optimisation of these vehicles. In this paper, we propose a design loop that makes use of surrogate modelling and AM to reduce the design and optimisation time of scientific sUAS. AM reduces the time and effort required to fabricate a complete aircraft, allowing for rapid design iterations and flight testing. Co-Kriging surrogate models allow data collected from test flights to correct Kriging models trained with numerically simulated data. The resulting model provides physically accurate and computationally cheap aircraft performance predictions. A global optimiser is used to search this model to find an optimal design for a bespoke aircraft. This paper presents the design loop and a case study which demonstrates its application.

Unmanned Air Systems (UAS) navigate using Global Navigation Satellite Systems (GNSS), but GNSS vulnerability precludes its use as the only means of navigation and requires a secondary means of navigation. A differentiating characteristic of UAS is their periodic communications with the ground station. This paper analyses the adequacy of employing UAS Command, Control and Communications (C3) as a secondary means of navigation. With no additional infrastructure, an Extended Kalman Filter (EKF) is used to process C3 messages and to obtain the positions of the UAS. Navigation accuracy and integrity are calculated in a scenario with three UAS. The obtained results meet the International Civil Aviation Organization (ICAO) Performance-Based Navigation (PBN) requirements.

The aim of the paper is to inform design staffs on potential Remotely Piloted Air Systems (RPAS) improvements to afford greater utility on the battlespace. The scope of the paper covers Air Warfare Centre experiences working with several NATO Class II RPAS. Using an ‘assurance framework’ that examines integrity of the aircraft, the operational environment and crew competency, the paper identifies what changes need to be made if the utility of RPAS in this category is to be enhanced.