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V-Formation and echelon formation flights can be seen used by migratory birds throughout the year and have left many scientists wondering why they choose very specific formations. Experiments and analytical studies have been completed on the topic of the formation flight of birds and have shown that migratory birds benefit aerodynamically by using these formations. However, many of these studies were completed using fixed-wing models, while migratory birds both flap and glide while in formation. This paper reports the design of and experiments with a flapping-wing model rather than only a fixed-wing model. In order to complete this study, two different approaches were used to generate a flapping-wing model. The first was a computational study using an unsteady vortex–lattice (UVLM) solver to simulate flapping bodies. The second was an experimental design using both custom-built flapping mechanisms and commercially bought flapping drones. The computations and various experimental trials confirmed that there is an aerodynamic benefit from flying in either V-formation or echelon flight while flapping. It is shown that each row of birds experiences an increase in aerodynamic performance based on positioning within the formation.

Elucidating the adaptations that promote flight in animals can aid the understanding of evolution and species divergence, and/or provide inspiration for aerospace engineering and the design of better aerial vehicles. The famed long-distance migration of monarch butterflies in North America still holds many questions and opportunities for inspiration. For example, there is little research on whether the monarch’s primary wing colors themselves (black, orange, or white) have any aerodynamic or migration function. Dark colors on wings of other animals have recently been shown to aid flight by enhancing solar absorption, which reduces drag forces. However, too much black surface could be problematic for monarchs, which are exposed to increasing amounts of solar energy along their flightpath. This paper describes the results of two related investigations that attempt to elucidate the importance of wing color to the monarch migration. By measuring the color proportions of nearly 400 monarch wings collected at different stages of their journey, we found, surprisingly, that successful migrants tended to have less black on their wings (about 3% less), but also more white pigment (about 3% more); monarchs have a band of light-colored marginal wing spots. Second, image analysis of museum specimens revealed migratory monarchs had significantly larger white spots, proportional to the wing area, than most non-migratory, New World Danaid butterflies, which argues spot size has evolved along with migratory behavior. Combined, these findings strongly suggest that the long-distance migration itself selects for larger white spots every fall, so that only those individuals with large spots will survive to pass on their genes. Further experimental work is needed to elucidate how the spots aid the migration, but it is possible that they enhance aerodynamic efficiency; other work by the authors demonstrates how alternating white and black pigment on wings can reduce drag. These results will serve as a useful starting point for such endeavors, which should improve understanding of one of the world’s most fascinating animal migrations, and also provide practical knowledge for the field of aerospace engineering.

This paper reviews a majority of the nature-inspired algorithms, including heuristic and meta-heuristic bio-inspired and non-bio-inspired algorithms, focusing on their source of inspiration and studying their potential applications in drones. About 350 algorithms have been studied, and a comprehensive classification is introduced based on the sources of inspiration, including bio-based, ecosystem-based, social-based, physics-based, chemistry-based, mathematics-based, music-based, sport-based, and hybrid algorithms. The performance of 21 selected algorithms considering calculation time, max iterations, error, and the cost function is compared by solving 10 different benchmark functions from different types. A review of the applications of nature-inspired algorithms in aerospace engineering is provided, which illustrates a general view of optimization problems in drones that are currently used and potential algorithms to solve them.

Unmanned air vehicle (UAV) systems for performing forestry applications have expanded in recent decades and have great economic benefits. They are validated to be more appealing than traditional platforms in various aspects, such as repeat rate, spatial resolution, and accuracy. This paper consolidates the state-of-the-art unmanned systems in the forestry field with a major focus on UAV systems and heterogeneous platforms, which are applied in a variety of forestry applications, such as wood production, tree quantification, disease control, wildfire management, wildlife conservation, species classification, etc. This review also studies practical applications under multiple forestry environments, including wild and managed forests, grassland, urban green parks, and stockyards. Special forest environments and terrains present customized demands for unmanned systems. The challenges of unmanned systems deployment are analyzed from environmental characterization, maneuverability and mobility improvement, and global regulatory interpretation. To better apply UAV systems into forestry, future directions are analyzed in terms of mobility enhancement and customized sensory adaption, which need to be further developed for synchronizing all possible agents into automatic functioning systems for forestry exploration.

Subterranean openings, including mines, present a unique and challenging environment for robots and autonomous exploration systems. Autonomous robots that are created today will be deployed in harsh and unexplored landscapes that humanity is increasingly encountering in its scientific and technological endeavors. Terrestrial and extraterrestrial environments pose significant challenges for both humans and robots: they are inhospitable and inaccessible to humans due to a lack of space or oxygen, poor or no illumination, unpredictable terrain, a GPS-denied environment, and a lack of satellite imagery or mapping information of any type. Underground mines provide a good physical simulation for these types of environments, and thus, can be useful for testing and developing highly sought-after autonomous navigation frameworks for autonomous agents. This review presents a collective study of robotic systems, both of individual and hybrid types, intended for deployment in such environments. The prevalent configurations, practices for their construction and the hardware equipment of existing multi-agent hybrid robotic systems will be discussed. It aims to provide a supplementary tool for defining the state of the art of coupled Unmanned Ground Vehicle (UGV)–Unmanned Aerial Vehicle (UAV) systems implemented for underground exploration and navigation purposes, as well as to provide some suggestions for multi-agent robotic system solutions, and ultimately, to support the development of a semi-autonomous hybrid UGV–UAV system to assist with mine emergency responses.

The mining industry has recently shown increased interest in drones for routine activities in underground and surface mines. Designing a drone for coal mines is extremely complicated since the Mine Safety and Health Administration (MSHA) has tight guidelines for any equipment that can be used in underground coal mines. Due to these criteria, designing a drone for underground coal mining is exceedingly difficult. This paper explores the challenges of creating an intrinsically safe drone propulsion system. To address the challenges of designing an intrinsically safe drone’s propulsion system for an underground coal mine, this work aims to investigate the potential approaches to enhance efficiency and mitigate the heat. The study begins with the drone’s sizing approach before moving on to the experimental setup that is utilized to test the drone’s propulsion system. Finally, answers to numerous issues arising during the inquiry are offered, and these solutions are empirically explored.

The increase in the number of Unmanned Aerial Vehicles (UAVs) and Micro Air Vehicles (MAVs), which are used in a variety of applications has led to a surge in low Reynolds number aerodynamics research. Flow around fixedwing MAVs has an unusual behavior due to its low aspect ratio and operates at low Reynolds number, which demanded to upgrade the used wind tunnel for this study. This upgrade enables measuring the small aerodynamics forces and moment of fixed-wing MAVs. The wind tunnel used in this work is upgraded with a state of art data acquisition system to deal with the different sensors signals in the wind tunnel. For accurate measurements, the sting balance, angle sensor, and airspeed sensor are calibrated. For validation purposes, an experiment is made on a low aspect ratio flat plate wing at low Reynolds number, and the measured data are corrected and compared with published results. The procedure presented in this paper for the first time gave a detailed and complete guide for upgrading and calibrating old wind tunnel, all the required corrections to correct the measured data was presented, the turbulence level correction new technique presented in this paper could be used to estimate the flow turbulence effect on the measured data and correct the measured data against published data. First published online 17 February 2020

Small-scale unmanned aerial vehicles are being deployed in urban areas for missions such as ground target tracking, crime scene monitoring, and traffic management. Aerial vehicles deployed in such cluttered environments are required to have robust autonomous navigation with both target tracking and obstacle avoidance capabilities. To this end, this work presents a simple-to-design but effective steerable sensor platform and its implementation techniques for both obstacle avoidance and target tracking. The proposed platform is a 2-axis gimbal system capable of roll and pitch/yaw. The mathematical model that governs the dynamics of this platform is developed. The performance of the platform is validated through a software-in-the-loop simulation. The simulation results show that the platform can be effectively steered to all regions of interest except backward. With its design layout and mount location, the platform can engage sensors for obstacle avoidance and target tracking as per requirements. Moreover, steering the platform in any direction does not induce aerodynamic instability on the unmanned aerial vehicle in mission.

This paper aims to provide a comprehensive review of the current state of drone technology and its applications in the mining industry. The mining industry has shown increased interest in the use of drones for routine operations. These applications include 3D mapping of the mine environment, ore control, rock discontinuities mapping, postblast rock fragmentation measurements, and tailing stability monitoring, to name a few. The article offers a review of drone types, specifications, and applications of commercially available drones for mining applications. Finally, the research needs for the design and implementation of drones for underground mining applications are discussed.

In this study, a novel simple strategy is proposed to choose and accommodate an airfoil based on the effects of airfoil type and plan-form shape on the flight performance of a micro air vehicle. In this strategy, after defining flight mission, the weight of the micro air vehicle is estimated and then, aerodynamic parameters and thrust force are calculated. In the next step, some different plan-forms and airfoils are investigated to be selected for decreasing the stall region in high attack anglesby open source software named XFLR5. Having calculated the aerodynamic center, the pitching moment needed to stabilize the micro air vehicle is computed. Due to the static margin, the airfoil camber line is changed to stabilize the micro air vehicle and then, its thickness is improved to reach to a high aerodynamic characteristic. To evaluate the software results, some flight tests are performed which then compared to the software results that show a good agreement. Finally, some adjustments and improvements are made on the micro air vehicle and then, its performance is obtained by the flight tests. The flight test results show it has an excellent aerodynamic performance, stability and maneuverability.

The development of new concepts for smart cities and the application of drones in this area requires different architecture for the drones’ stations (nests) and their placement. Drones’ stations are designed to protect drones from hazards and utilize charging mechanisms such as solar cells to recharge them. Increasing the number of drones in smart cities makes it harder to find the optimum station for each drone to go to after performing its mission. In classic ordered technique, each drone returns to its preassigned station, which is shown to be not very efficient. Greedy and Kuhn−Munkres (Hungarian) algorithms are used to match the drone to the best nesting station. Three different scenarios are investigated in this study; (1) drones with the same level of energy, (2) drones with different levels of energy, and (3) drones and stations with different levels of energy. The results show that an energy consumption reduction of 25−80% can be achieved by applying the Kuhn−Munkres and greedy algorithms in drone−nest matching compared to preassigned stations. A graphical user interface is also designed to demonstrate drone−station matching through the Kuhn−Munkres and greedy algorithms.

A new strategy is proposed in order to effectively design the components of actuation mechanisms for flapping wing micro air vehicles. To this end, the merits and drawbacks of some existing types of conventional flapping actuation mechanisms are first discussed qualitatively. Second, the relationships between the design of flapping wing actuation mechanism and the entrance requirements including the upstroke and downstroke angles and flapping frequency are determined. The effects of the components of the actuation mechanism on the kinematic and kinetic parameters are investigated. It is shown that there are optimum values for different parameters in order to design an efficient mechanism. Considering the optimized features for an actuation mechanism, the design, analysis, and fabrication of a new hybrid actuation mechanism for FWMAV named “Thunder I” with fourteen components consisting of two six-bar mechanisms are performed. The results show that this designed hybrid actuation mechanism has high symmetrical flapping motion with hinged connections for all components. The proposed methodology for the modeling and fabrication of Thunder I’s actuation mechanism can be utilized as guidelines to design efficient FWMAVs actuation mechanisms.