Unmanned Systems

This paper offers an alternative Casualty Area assessment. This parameter appears in all flying vehicles risk evaluation. This work arises from the intention of contributing to the subject of risk assessment in aviation. All the formulations of the Casualty Area — which will be analyzed in this paper — are tailored for debris with high kinetic energies. These models lead to an overestimation of the risk associated with small drones flight, preventing both their use and the implied operational benefits. The proposed version tailors the small Remotely Piloted Aircraft Systems (commonly known as drones) falling under the A2 European Aviation Safety Agency (EASA) category, C2 class [European Aviation Safety Agency, Civil drones (Unmanned aircraft, 2018), https://www.easa.europa.eu/easa-and-you/civil-drones-rpas, accessed November (2019)], i.e. drones with a mass up to 4 kg. To obtain the new formulation, the authors started with the most used formula, proposed by Montgomery [R. M. Montgomery and J. A. Ward, Casualty Areas from Impacting Inert Debris for People in the Open (Research Triangle Institute, 1995)], used by FAA (Federal Aviation Administration, [Range Safety Group, Common Risk Criteria for National Test Ranges Inert Debris (Range Commanders Council, 2000)] and [Range Safety Group, Common Risk Criteria Standards for National Test Ranges (Range Commanders Council, 2010)]), adopting new hypotheses but following the same process. The results allow a risk formulation more suitable for drones of the above-mentioned size [Range Safety Group, Range Safety Criteria For Unmanned Air Vehicles Supplement (Range Commanders Council, 1999)]. The proposed formulation can be of use for specific regulatory issues. As a matter of fact, many services use small drones: aerial photography during public assemblies, concerts, sporting events, home deliveries, buildings thermal evaluation, to name just a few. The implementation of the present results allows a wider series of operations previously restricted due to the estimation of an incompatible level of risk. In fact, with the new formulation of the Casualty Area, the level of risk is safely lowered, mainly addressing the small dimension drones [European Aviation Safety Agency, Civil drones (Unmanned aircraft), https://www.easa.europa.eu/easa-and-you/civil-drones-rpas, Online accessed November (2019)]. The steps leading to the final formulation derive from a comprehensive analysis, coherent with the guidelines set by FAA and EASA.

Coordination between unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) has received increasing attention in recent years. The list of successful applications of UAV–UGV coordination systems is growing and demonstrates that UAV–UGV coordination can provide real-world solutions that other types of coordination cannot offer. This paper systematically reviews the advances in UAV–UGV coordination systems during the period of 2015–2020 and offers a comprehensive investigation and analysis of the recent research. First, the essential elements in the UAV–UGV coordination systems are analyzed, and four key functional roles are identified. The close collaboration among functional roles can achieve the UAV–UGV coordination on perception, task, and motion. From the perspective of functional roles, UAV–UGV coordination systems can be further classified into eight categories. The functional-role-based category provides novel insights into analyzing various patterns of UAV–UGV coordination. This paper also discusses the challenges related to UAV–UGV coordination.

This paper focuses on offline navigation in quadcopters (Return-to-Home), autonomously in GPS Denied Areas or in cases that the aircraft loses GPS Signal by using the Haversine’s Great circle formula to calculate distance and direction. The internal sensors are used to estimate offsets for distance and direction. A control system modification is proposed, resulting in a high success rate with the several tests using a quadcopter with a Pixhawk flight controller, equipped with PX4FLOW.

Intelligent unmanned systems have important applications, such as pesticide-spraying in agriculture, robot-based warehouse management systems, and missile-firing drones. The underlying assumption behind all autonomy is that the agent knows its relative position or egomotion with respect to some reference or scene. There exist thousands of localization systems in the literature. These localization systems use various combinations of sensors and algorithms, such as visual/visual-inertial SLAM, to achieve robust localization. The majority of the methods use one or more sensors from LIDAR, camera, IMU, UWB, GPS, compass, tracking system, etc. This survey presents a systematic review and analysis of published algorithms and techniques chronologically, and we introduce various highly impactful works. We provide insightful investigation and taxonomy on sensory data forming principle, feature association principle, egomotion estimation formation, and fusion model for each type of system. At last, some open problems and directions for future research are also included. We aim to survey the literature comprehensively to provide a complete understanding of localization methodologies, performance, advantages and limitations, and evaluations of various methods, shedding some light for future research.

Unmanned aerial systems provide many applications with the ability to perform flying tasks autonomously, and hence have received significant research and commercial attention in the past decade. One of the most popular unmanned aerial platforms for such tasks is the small-scale rotorcraft with multiple rotors, commonly known as multicopters. In order for these platforms to perform fully autonomous missions and tasks, they require a sophisticated low-level flight control system that is integrated with advanced task and motion planning modules, which combine together to form the complete unmanned aerial system (UAS). In this paper, the planning module of unmanned multicopter systems is discussed in detail, and a comprehensive survey on techniques for both motion and task planning reported in literature and by the Unmanned Systems Research Group at the National University of Singapore is presented.