Multi-rotor Drone Research Articles

Challenges of collecting blow from small cetaceans

AbstractWe trialed the collection of blow samples using a waterproof electric multirotor (quadcopter) drone from two free‐ranging dolphin species, the abundant and approachable bottlenose dolphin (Tursiops aduncus) and the less common and boat shy humpback dolphin (Sousa sahulensis). This drone was fast, maneuverable, and quiet compared to other drones commonly used in studies of cetaceans and relative to their hearing thresholds. We were successful in collecting blow samples from four individual dolphins (three bottlenose dolphins and one humpback dolphin) in two groups. The success of obtaining samples was dependent on the individual dolphin's activity. We were successful in sampling when dolphins were resting and socializing but found that socializing dolphins were not predictable in their surfacing and direction and therefore do not recommend drone sampling socializing dolphins. The suitability and preference of the sampling technique over biopsy sampling is highly dependent on the dolphin activity. We also attempted to extract DNA from the blow samples with the aim of assessing the feasibility of using blow sampling by drone for population genetic studies. We were unsuccessful in extracting DNA and recommend that others attempting to sample dolphin blow with a drone should prioritize collecting a larger volume of blow that may yield adequate concentrations of DNA to be amplified. Blow sample volume could potentially be increased by sampling with more absorbent materials.

Structure from motion photogrammetry in ecology: Does the choice of software matter?

Image‐based modeling, and more precisely, Structure from Motion (SfM) and Multi‐View Stereo (MVS), is emerging as a flexible, self‐service, remote sensing tool for generating fine‐grained digital surface models (DSMs) in the Earth sciences and ecology. However, drone‐based SfM + MVS applications have developed at a rapid pace over the past decade and there are now many software options available for data processing. Consequently, understanding of reproducibility issues caused by variations in software choice and their influence on data quality is relatively poorly understood. This understanding is crucial for the development of SfM + MVS if it is to fulfill a role as a new quantitative remote sensing tool to inform management frameworks and species conservation schemes. To address this knowledge gap, a lightweight multirotor drone carrying a Ricoh GR II consumer‐grade camera was used to capture replicate, centimeter‐resolution image datasets of a temperate, intensively managed grassland ecosystem. These data allowed the exploration of method reproducibility and the impact of SfM + MVS software choice on derived vegetation canopy height measurement accuracy. The quality of DSM height measurements derived from four different, yet widely used SfM‐MVS software—Photoscan, Pix4D, 3DFlow Zephyr, and MICMAC, was compared with in situ data captured on the same day as image capture. We used both traditional agronomic techniques for measuring sward height, and a high accuracy and precision differential GPS survey to generate independent measurements of the underlying ground surface elevation. Using the same replicate image dataset (n = 3) as input, we demonstrate that there are 1.7, 2.0, and 2.5 cm differences in RMSE (excluding one outlier) between the outputs from different SfM + MVS software using High, Medium, and Low quality settings, respectively. Furthermore, we show that there can be a significant difference, although of small overall magnitude between replicate image datasets (n = 3) processed using the same SfM + MVS software, following the same workflow, with a variance in RMSE of up to 1.3, 1.5, and 2.7 cm (excluding one outlier) for “High,” “Medium,” and “Low” quality settings, respectively. We conclude that SfM + MVS software choice does matter, although the differences between products processed using “High” and “Medium” quality settings are of small overall magnitude.

Deep Learning-Based Real-Time Multiple-Object Detection and Tracking from Aerial Imagery via a Flying Robot with GPU-Based Embedded Devices.

In recent years, demand has been increasing for target detection and tracking from aerial imagery via drones using onboard powered sensors and devices. We propose a very effective method for this application based on a deep learning framework. A state-of-the-art embedded hardware system empowers small flying robots to carry out the real-time onboard computation necessary for object tracking. Two types of embedded modules were developed: one was designed using a Jetson TX or AGX Xavier, and the other was based on an Intel Neural Compute Stick. These are suitable for real-time onboard computing power on small flying drones with limited space. A comparative analysis of current state-of-the-art deep learning-based multi-object detection algorithms was carried out utilizing the designated GPU-based embedded computing modules to obtain detailed metric data about frame rates, as well as the computation power. We also introduce an effective target tracking approach for moving objects. The algorithm for tracking moving objects is based on the extension of simple online and real-time tracking. It was developed by integrating a deep learning-based association metric approach with simple online and real-time tracking (Deep SORT), which uses a hypothesis tracking methodology with Kalman filtering and a deep learning-based association metric. In addition, a guidance system that tracks the target position using a GPU-based algorithm is introduced. Finally, we demonstrate the effectiveness of the proposed algorithms by real-time experiments with a small multi-rotor drone.

3D CITY MODELING USING MULTIROTOR DRONE FOR CITY HERITAGE CONSERVATION

This paper aims to construct a 3D Malay city based on data collected from DJI Phantom 3, a multi rotor drone, and further analyse the urban form of traditional Malay cities using 3 main urban form components which are buildings, land use and streets. Kota Bharu was selected as the study area and the flight mission produced 793 images which were processed in Agisoft and further constructed 3D GIS in ArcGIS 10.2. The analysis of urban form shows that the old traditional development in north-north west still maintain the identity of Malay urban form, of the organic pattern of streets, preserve Malay architectures and the type of land use for traditional settlement. This finding shows that, Malay values in cities and architecture still remain and it must be preserved from any development and it can be a benchmark on adapting technologies and shifting methods in conservation and safeguarding our heritage cities in Malaysia.

Characterization of digital MEMS microphone elements for usage in a hostile fire detection system on a multi-rotor drone

Acoustic based Hostile Fire Detection Systems (HFDS) depend on multi-element arrays of microphones which are simultaneously sampled at sample rates often in the 10–50 ksps range. A driving component of the electronic hardware complexity of the system is the signal buffering, filtering, and analog to digital conversion required for each microphone channel. Digital MEMS microphones consolidate these functions to within the microphone element giving a digital output representative of the measured acoustic signal. Digital MEMS microphones allow for a completely digital hardware solution which reduces complexity and allows more flexibility in utilizing higher element number arrays if desired. The performance parameters relevant to HFDSs of current best-in-class digital MEMS microphones were measured and compared to current analog microphones commonly utilized in these systems. The purpose of these tests was to determine the viability of digital MEMS microphones as an alternate acoustic sensing element for a HFDS system being implemented on a multi-rotor drone.

Beach safety: can drones provide a platform for sighting sharks?

Abstract ContextA series of unprovoked shark attacks on New South Wales (Australia) beaches between 2013 and 2015 triggered an investigation of new and emerging technologies for protecting bathers. Traditionally, bather protection has included several methods for shark capture, detection and/or deterrence but has often relied on environmentally damaging techniques. Heightened environmental awareness, including the important role of sharks in the marine ecosystem, demands new techniques for protection from shark attack. Recent advances in drone-related technologies have enabled the possibility of real-time shark detection and alerting. AimTo determine the reliability of drones to detect shark analogues in the water across a range of environmental conditions experienced on New South Wales beaches. MethodsA standard multirotor drone (DJI Inspire 1) was used to detect shark analogues as a proxy during flights at 0900, 1200 and 1500 hours over a 3-week period. The 27 flights encompassed a range of environmental conditions, including wind speed (2–30.0kmh−1), turbidity (0.4–6.4m), cloud cover (0–100%), glare (0–100%), seas (0.4–1.4m), swells (1.4–2.5m) and sea state (Beaufort Scale 1–5 Bf). Key resultsDetection rates of the shark analogues over the 27 flights were significantly higher for the independent observer conducting post-flight video analysis (50%) than for the drone pilot (38%) (Wald P=0.04). Water depth and turbidity significantly impaired detection of analogues (Wald P=0.04). Specifically, at a set depth of 2m below the water surface, very few analogues were seen by the observer or pilot when water turbidity reduced visibility to less than 1.5m. Similarly, when water visibility was greater than 1.5m, the detection rate was negatively related to water depth. Conclusions The present study demonstrates that drones can fly under most environmental conditions and would be a cost-effective bather protection tool for a range of user groups. ImplicationsThe most effective use of drones would occur during light winds and in shallow clear water. Although poor water visibility may restrict detection, sharks spend large amounts of time near the surface, therefore providing a practical tool for detection in most conditions.

Human tracking of multi-rotor drone by deep learning

Human tracking of multi-rotor drone by deep learning

Electromagnetic image of small UAV in very low frequency range

Abstract The article deals with the measurement, visualization and analysis of the magnetic field in the 3D space around a small quadcopter. The measurements were realized in the very low frequency (VLF) range, since this range is interesting because of the possible detection of the drone also in the fully automated flight mode (without telemetry transmission). A measurement equipment/device that allows mapping of the magnetic field of the multirotor drone based on the sensor elevation and the copters azimuth was realized. The magnetic field was measured with a small inductive sensor – the air coil. Frequency analysis (signal spectrum) and the spatial 3D analysis of the selected frequency components that brought interesting results were carried out on the recorded data.

End-to-End Analysis and Design of a Drone Flight Controller

Timing guarantees are crucial to embedded and cyber-physical applications that must bound the end-to-end delay between sensing, processing and actuation. For example, in a flight controller for a multirotor drone, the data from a gyro or inertial sensor must be gathered and processed to determine the attitude of the aircraft. Sensor data fusion is followed by control outputs that alter rotor speeds to adjust the drone’s flight. If the processing pipeline between sensor input and actuation is not bounded, the drone will lose control and possibly fail to maintain flight. This paper describes a composable pipe model for sensor data processing and actuation tasks. The pipe model is used to analyze two end-to-end semantics: 1) freshness and 2) reaction time. We provide a mathematical framework to derive feasible task periods and budgets that satisfy both schedulability and end-to-end timing requirements. We demonstrate the applicability of our design approach by using it to port the Cleanflight flight controller firmware to our in-house real-time operating system called Quest. Experiments show that Cleanflight ported to Quest is able to achieve end-to-end latencies within the predicted time bounds derived by analysis.

ATMOSPHERIC ENVIRONMENT DETECTION METHOD BASED ON MULTI-ROTOR UAV PLATFORM

Abstract. For the method of atmospheric detection based on multi-rotor UAV, the effects of flight safety and airflow on detection accuracy are analyzed. The detector mounted on the multi-rotor drone should be highly symmetrical and the center of gravity should be on the same vertical line as the center of gravity of the drone. Mounting the detector above the drone's fuselage will reduce the stability of the drone, and lowering it will improve stability, but for models with high stability, placing it below will affect the maneuverability of the drone. The airflow interference in the area where the detector can be placed near the fuselage is related to the drone: the faster the rotor speed, and the closer the rotor is to the fuselage, the stronger the airflow interference. At the same time, the influence of airflow disturbance on temperature and humidity has a gradual process. Waiting for a period of time after starting the drone can change the error into a fixed error for post-processing. This method was used to detect a pollution process and achieved good results.

Multiple Rotors Hovering Near an Upper or a Side Wall

The influence of walls on the performance of multiple rotor type drones is numerically simulated. With the current wide-spread applications of autonomously flyable UAVs, there are potential needs to use the drones for inspections and observation near various structures, such as buildings and bridges. The flow fields around multiple rotors are influenced significantly by the existence of an upper or a side wall, so that the thrust, required torque, and other forces and moments are changed. It is found that when a rotor approaches an upper wall, as the distance between the rotor and the upper wall is less than a diameter of the rotor, the thrust suddenly increases, which causes the rotors to collide with the upper wall. When an isolated rotor is operated near a side wall, the thrust decreases and a rolling moment appears to tilt the rotor toward the wall as the distance becomes shorter. For a multiple rotor drone near a side wall, the rotors have different distances from the wall, which causes the whole aircraft tilts toward the wall. From the perspective of safety operations, the multi-rotor drone should be kept away from both the upper wall and the side wall at a distance of at least 1.5 times of the rotor diameter to prevent unexpected motions of the aircraft caused by the wall during hovering flight.

Drone 3D mapping in identifying Malay urban form: case study of Kota Bharu

Malay city was one of the oldest civilization in the world which contains unique identity of architecture, the urban design characteristic and the urban form of city planning. Kota Bharu was an example for one of the Malay city which contains the historical building which originally build from 1840 onwards that still exist in peninsular Malaysia. The location of the a few main and significant historical building scattered around the Istana Balai Besar Kelantan proved that, the area was one of the originally Malay city existed in Malaysia. This paper attempt to map an urban form and identify a historical building in Kota Bharu using Multirotor drone. Phantom 3 was used to carry out the aerial mapping and further proceed for 3D modelling at 500meter radius from the centre of study area Istana Balai Besar. the analysis of current pattern of the city, distribution of the land use and building height for the study area shows that the area still preserve the traditional Malay city element and shows the different in urban pattern between the Malay traditional city and area with the influence from the British government and planning for the area. This result proof that the use of drone in mapping and modelling helps in analyse for the urban form and building height for city area in collecting data especially for the aerial mapping. The integration between Urban Planning, GIS, and 3D are highlighted as the platform for the analysis tool and data storage.

Vertical profiles of lung deposited surface area concentration of particulate matter measured with a drone in a street canyon

The vertical profiles of lung deposited surface area (LDSA) concentration were measured in an urban street canyon in Helsinki, Finland, by using an unmanned aerial system (UAS) as a moving measurement platform. The street canyon can be classified as an avenue canyon with an aspect ratio of 0.45 and the UAS was a multirotor drone especially modified for emission measurements. In the experiments of this study, the drone was equipped with a small diffusion charge sensor capable of measuring the alveolar LDSA concentration of particles. The drone measurements were conducted during two days on the same spatial location at the kerbside of the street canyon by flying vertically from the ground level up to an altitude of 50 m clearly above the rooftop level (19 m) of the nearest buildings. The drone data were supported by simultaneous measurements and by a two-week period of measurements at nearby locations with various instruments. The results showed that the averaged LDSA concentrations decreased approximately from 60 μm2/cm3 measured close to the ground level to 36–40 μm2/cm3 measured close to the rooftop level of the street canyon, and further to 16–26 μm2/cm3 measured at 50 m. The high-resolution measurement data enabled an accurate analysis of the functional form of vertical profiles both in the street canyon and above the rooftop level. In both of these regions, exponential fits were used and the parameters obtained from the fits were thoroughly compared to the values found in literature. The results of this study indicated that the role of turbulent mixing caused by traffic was emphasized compared to the street canyon vortex as a driving force of the dispersion. In addition, the vertical profiles above the rooftop level showed a similar exponential decay compared to the profiles measured inside the street canyon.

A study of atmospheric mixing of trace gases by aerial sampling with a multi-rotor drone

We exploited a novel sampling vehicle, a multi-rotor drone carrying a remote-controlled whole air sampling device, to collect aerial samples with high sample integrity and preservation conditions. An array of 106 volatile organic compounds (VOCs), CO, CH4, and CO2 were analyzed and compared between the aerial samples (300-m height) and the ground-level samples in pairs to inspect for vertical mixing of the trace gases at a coastal site under three different meteorological conditions of local circulation, frontal passage, and high-pressure peripheral circulation. A rather homogeneous composition was observed for the sample pairs immediately after the frontal passage, indicating a well-mixed condition below 300 m. In contrast, inhomogeneous mixing was observed for the sample pairs under the other two conditions (local circulation and high-pressure peripheral circulation), suggesting different layers of air masses. Furthermore, information of unique source markers, composition profiles, and lifetimes of compounds were used to differentiate the origins of the air masses aloft and at the surface to substantiate the observed inhomogeneity. The study demonstrates that, with the availability of the near-surface aerial sampling coupling with in-laboratory analysis, detailed compositions of trace gases can now be readily obtained with superior data quality. Based on the distinctive chemical compositions, the sources, transport, and atmospheric mixing of the airborne pollutants in the near-surface atmosphere can be better studied and understood.

Applications of multirotor drone technologies in construction management

ABSTRACTMultirotor drones are considered a new and innovative technology. Therefore, many fields are showing increasing interest in utilizing multirotor drones, such as mapping in mining and surveillance in transportation. The construction industry has been a slow adopter of novel technologies. However, multirotor drones have potential to facilitate construction in many aspects. There is, therefore, a need to extensively research their applications and analyze their roles in construction engineering and management. This paper aims to comprehensively investigate the current applications of multirotor drones, analyze their benefits and explore their potential in the future of the construction industry. Several main aspects are reviewed and discussed, namely land surveying, logistics, on-site construction, maintenance and demolition. The results reveal that the main contributions are work safety, cost-effectiveness and carbon emission reduction, while there are possible adverse impacts on the basis of current limitations of multirotor drones. However, it can be predicted that the usefulness of drones will continue to increase in the future of the construction industry. Thus, this study will benefit construction managers in raising awareness of the use of these emerging technologies and researchers in further exploring applications of multirotor drones in construction projects.

Multirotor Drone Noise at Static Thrust

A first principles understanding of the sound field produced by multirotor drones in hover is presented. Propeller diameters ranging from 8 to 12 in. are examined and with configurations comprising an isolated rotor, quadcopter, and hexacopter configuration. The drone pitch, defined as the ratio of drone diameter to rotor diameter, is the same for all multirotor configurations and is valued at 2.25. A six-degree-of-freedom load cell is used to assess the aerodynamic performance of each configuration, whereas an azimuthal array of in. microphones, placed between two and three hub-center diameters from the drone center, is used to assess the acoustic near field. The analysis is performed using standard statistical metrics such as sound pressure level and overall sound pressure level and is presented to demonstrate the relationship between the number of rotors, the drone rotor size, and its aerodynamic performance (thrust) relative to the near-field acoustics.

Measuring behavioral responses of sea turtles, saltwater crocodiles, and crested terns to drone disturbance to define ethical operating thresholds.

Drones are being increasingly used in innovative ways to enhance environmental research and conservation. Despite their widespread use for wildlife studies, there are few scientifically justified guidelines that provide minimum distances at which wildlife can be approached to minimize visual and auditory disturbance. These distances are essential to ensure that behavioral and survey data have no observer bias and form the basis of requirements for animal ethics and scientific permit approvals. In the present study, we documented the behaviors of three species of sea turtle (green turtles, Chelonia mydas, flatback turtles, Natator depressus, hawksbill turtles, Eretmochelys imbricata), saltwater crocodiles (Crocodylus porosus), and crested terns (Thalasseus bergii) in response to a small commercially available (1.4 kg) multirotor drone flown in Northern Territory and Western Australia. Sea turtles in nearshore waters off nesting beaches or in foraging habitats exhibited no evasive behaviors (e.g. rapid diving) in response to the drone at or above 20–30 m altitude, and at or above 10 m altitude for juvenile green and hawksbill turtles foraging on shallow, algae-covered reefs. Adult female flatback sea turtles were not deterred by drones flying forward or stationary at 10 m altitude when crawling up the beach to nest or digging a body pit or egg chamber. In contrast, flyovers elicited a range of behaviors from crocodiles, including minor, lateral head movements, fleeing, or complete submergence when a drone was present below 50 m altitude. Similarly, a colony of crested terns resting on a sand-bank displayed disturbance behaviors (e.g. flight response) when a drone was flown below 60 m altitude. The current study demonstrates a variety of behavioral disturbance thresholds for diverse species and should be considered when establishing operating conditions for drones in behavioral and conservation studies.

Toward a Secure Drone System: Flying With Real-Time Homomorphic Authenticated Encryption

Controlling or accessing remotely has become a prevalent form of operating numerous types of platforms and infrastructure. An exploding number of vehicles such as drones or cars, in particular, are being controlled wirelessly or connected through networks. This has brought unanimous concern that today’s networked vehicle systems are vulnerable to attacks and the results could be fatal. Unfortunately, in contrast to active investigation on the security of the vehicles themselves, sensors, or communication channels, existing approaches for these real-time, safety-critical systems do not take controllers into enough consideration. In order to protect the controller that performs the arithmetic operations using sensor measurements and generates command signals, we adopt homomorphic cryptography for the controller. It removes risks associated with the management of the secret key inside the controller, by eliminating the need to encrypt and decrypt the data for the mathematical operation within the controller. Specifically, we propose an efficient linearly homomorphic authenticated encryption ( LinHAE ) scheme for the ground control center of a multi-rotor drone, in a manner that enables real-time operation for safe autonomous flight. To facilitate the linear scheme, we design the ground controller targeted to allow state update using additions and multiplications by a system-specific constant. The proposed LinHAE guarantees the security against eavesdropping and forgery attacks, unlike homomorphic encryption alone that does not provide means to check whether the received signal at the drone side is authentic or compromised. We introduce a LinHAE with security and computational tractability, and describe how it can fit into the standard architecture for drone systems and how the specific controller is implemented. Building on these ingredients, we report the first successful operation of a multi-rotor flying robot that autonomously flies under the ground controller with real-time homomorphic authenticated encryption.

Estimating Tree Height and Diameter at Breast Height (DBH) from Digital Surface Models and Orthophotos Obtained with an Unmanned Aerial System for a Japanese Cypress (Chamaecyparis obtusa) Forest

Methods for accurately measuring biophysical parameters are a key component for quantitative evaluation regarding to various forest applications. Conventional in situ measurements of these parameters take time and expense, encountering difficultness at locations with heterogeneous microtopography. To obtain precise biophysical data in such situations, we deployed an unmanned aerial system (UAS) multirotor drone in a cypress forest in a mountainous area of Japan. The structure from motion (SfM) method was used to construct a three-dimensional (3D) model of the forest (tree) structures from aerial photos. Tree height was estimated from the 3D model and compared to in situ ground data. We also analyzed the relationships between a biophysical parameter, diameter at breast height (DBH), of individual trees with canopy width and area measured from orthorectified images. Despite the constraints of ground exposure in a highly dense forest area, tree height was estimated at an accuracy of root mean square error = 1.712 m for observed tree heights ranging from 16 to 24 m. DBH was highly correlated with canopy width (R2 = 0.7786) and canopy area (R2 = 0.7923), where DBH ranged from 11 to 58 cm. The results of estimating forest parameters indicate that drone-based remote-sensing methods can be utilized to accurately analyze the spatial extent of forest structures.

Analysis of preliminary design requirements of a heavy lift multirotor drone for agricultural use

Within the civil aviation cluster, the technological applications in agriculture represent a booming field consisting in acquisition of data through remote sensing and integration of sensor networks (crop status detection) or development of chemical and biological treatment applications. Drones in agriculture can be used for a variety of task, aimed to increase farm crop yields and accurately monitor fields, simultaneously decreasing time, labour and resources. While for some specific task a medium size drone can be chosen, on the other hand for other task like precision spraying of pesticide or fertilizer heavy lift drone are required. Prior to the approval of Yamaha R-MAX, an UAV helicopter which will be allowed to operate with a maximum payload of 98 kg, the Federal Aviation Administration (FAA) had only issued exemptions for much smaller drones weighing less than 55 pounds (24.98 kg). In Europe national legislations still lack of harmonization, and in Italy at the moment the local legislation restricts the possible choices to a maximum allowed take-off weight of 25kg without the necessity to submit a “permit to fly” documentation which is equivalent to the one required for a full scale commercial vehicle. Depending on the required task, one of the more important tasks of designing a multirotor Unmanned Aerial Vehicle (UAV) is the selection of a propulsion system that will provide desired performance in terms of payload and flight length or duration. Rigorous methods for selecting these drive components, that is, the motors, propellers, and batteries for electric UAVs are not readily available. A possible choice relies on using a Ready To Fly (RTF) UAV, but rapid changes in components and a fast evolution of the performance of engines and batteries allow possible updates of the existing UAV using aftermarket part to increase the flight envelope, a particularly interesting feature for heavy lift drone if a proper design method is adopted. Moreover, integration of technologies like LIDAR is easier to implement on UAV in which the design is not proprietary. In this work the technical requirements for agricultural tasks are investigated, and the state of the art of drone design method is presented, reporting an analysis of actual possibilities in terms of payload/flight envelope.