Top PDF Design and development of an unmanned aerial and ground vehicles for precision pesticide spraying

Design and development of an unmanned aerial and ground vehicles for precision pesticide spraying

Design and development of an unmanned aerial and ground vehicles for precision pesticide spraying

Plant diseases are one of the major problems for crop yields. Pesticide chemicals are commonly used in traditional pest control to protect plants from these diseases in agriculture (TCTOB 2017). The most common method of pest control is the usage of pesticides that either kill pests or inhibit their development (Sarwar 2015). Pesticide consists of chemicals to remove the harmful effects of pests from a diseased plant. Half of all pesticides that common in agricultural applications are used on the five main crops, cereals, corn, rice, cotton and soya. It is a well-known fact that the hazards of chemical pesticide usage, although statistics are difficult to gather about its hazardous. According to the World Health Organization (WHO), pesticides are causing more than 200,000 root losses every year and poisoning at least three million people. It is estimated that about 25 million agricultural workers are poisoned from spraying applications every year (Abdou 2018; Jeyaratnam 1990). Present chemical pesticides used in spraying applications are much more fading, but they may consist of highly toxic content to some non-target organisms. Pesticide leaks in watercourses mainly by way of direct spraying application, aerial spray drift and run-off from treated areas. Groundwater feeds soil and moves slowly and once its water sources are contaminated, they may remain so for many decades. Chemical pesticides are powerful and effective solutions for protecting farming fields. Usage of pesticides protects the crop health and improves the crop yield by increasing the farming efficiency. Mostly, farmers and foresters choosing the pesticide spraying method as a first option in order to protect farming fields from the diseases. In 1998, herbicides accounted for 49% of world pesticide use, followed by insecticides at 27%, fungicides at 20% et al. 4% (Wetzel, Duchesne, and Laporte 2006).
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Performances evaluation of four typical unmanned aerial vehicles used for pesticide application in China

Performances evaluation of four typical unmanned aerial vehicles used for pesticide application in China

Despite these preceding studies, almost all of the researches focused on the effect of working parameters on droplet deposition and biological efficacy [17] . High efficiency, especially the strong ability to deal with sudden disasters including plant diseases and insect pests with low risk, is one of the most important reasons for the greatly developed UAVs. However, there is no report on the evaluation of the working efficiency of UAVs for plant protection as a very important evaluation index. As an emerging technology, there are still a series of practical issues for UAV spraying for pest protection [9] , such as uniformity of droplet distribution, droplet coverage ratio, penetrability of pesticide into the crop canopy, and working efficiency of UAV. In order to identify the pesticides application performances and development status of UAVs in China, four typical UAVs for plant protection, sold in domestic market and tested by the National Plant Protection Machinery Testing Center, were tested in this research.
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Design and test of a six-rotor unmanned aerial vehicle (UAV) electrostatic spraying system for crop protection

Design and test of a six-rotor unmanned aerial vehicle (UAV) electrostatic spraying system for crop protection

These previous studies mainly focused on the effects of UAV operation parameters on the droplet deposition, and determined the optimal operation parameters for UAV crop protection via testing. However, these studies were based on different models and had different operational goals. As a result, the influencing rules were different, and it is difficult for determining the optimal operation parameters. In order to find a common method for improving droplet deposition, the electrostatic spray technology, which is widely deployed in ground crop protection machines, was considered applying to UAVs to effectively improve the droplet deposition on a target, thus reducing droplet drift [19-21] . For instance, He et al. [22] developed an electrostatic spray system for orchards, and field test results showed that charged droplets could prevent 50%-70% of the pesticide waste. In the United States of America, Kirk et al. [23] performed field electrostatic spray tests, the results showed that compared with conventional spray technology, electrostatic spray technology reduced droplet drift by 20%-30%. The first electrostatic nozzle for aerial spraying was developed by Calton and Isler [24] . The results from aerial spray tests showed that this device
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UAVs – Unmanned aerial vehicles in landscape practice

UAVs – Unmanned aerial vehicles in landscape practice

Figure 7: Drone Operator: Sky Cam East (James Hazell), Visualisation: Ubiety Landscape + Urban Design (Ramon Keeley). In this case, elected councillors who are responsible for determining detailed planning applications and the wider public as consultees often find it very difficult to visualise a proposed devel- opment from 2D plans and drawings. 3D artists impressions have typically helped overcome this, and in more recent years this has been augmented by the use of very detailed computer generated renderings. The more recent use of Unmanned Aerial Vehicles (UAVs) brings a further dimension to this in providing the affordable opportunity to visualise a proposed development within its surrounding environment when viewed from some alternative perspectives other than just ground level or existing adjacent struc- tures.
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Fault tolerant flight control system design for unmanned aerial vehicles

Fault tolerant flight control system design for unmanned aerial vehicles

There has been a gradual evolution of UAV mission roles from expendable target drones to expandable multi-mission aircraft with mission specifications extending to the more elaborate such as missile decoys, military reconnaissance, maritime surveillance, and even combat missions. UAVs are increasingly being used in front-line combat, that is, battlefield missions, to reduce hu- man casualties. In parallel, there are many civilian applications of UAVs, in meteorological and atmospheric research, border patrol, agricultural spraying and bush fire surveillance. A charac- teristic feature of current UAV flight missions is the decreasing reliance on human intervention to control the flight vehicle with a significant shift towards autonomous flight whereby the flight control decisions are executed by an on-board computer according to some pre-programmed flight plan. This autonomous characteristic has been made possible with the development of advanced flight control systems and autopilots capable of operating the aircraft with minimal human input. Thus, the mission requirements have been further extended to include the capa- bility of UAVs to fly long endurance flights in different environments.
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ROTORCRAFT Design & Development of an Unmanned Aerial Vehicle

ROTORCRAFT Design & Development of an Unmanned Aerial Vehicle

pesticides and sprayers can be attached above and beneath it respectively and can be used for Agricultural pesticide spraying application and also can be used like the conventional ones for photography in the meanwhile. Hence, multiple applications can be performed using this single model.

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Terrain Mapping From Unmanned Aerial Vehicles

Terrain Mapping From Unmanned Aerial Vehicles

In land surveying, a number of conventional devices have been used in producing terrain mapping particularly DTM and DSM. There are such as total station [1], global positioning system (GPS) [2], light detection ranging radar (LiDAR) [3-4], manned aircraft [5-6], terrestrial laser scanning (TLS) [7] and remote sensing [8-9]. However, despite have been benefitted many, these approaches suffer from certain limitations particularly in terms of time consumption, usage and costing. The issue is much more serious in the tropical regions which are known persistently covered with clouds especially during monsoon seasons, making it difficult to capture high-quality images even by using remote sensing satellite technology. Meanwhile, GPS survey requires a lot of time to establish high-density points in the study area. This is because GPS survey method measures discrete point on the surface. Therefore, this method is not practical for projects allocated with limited budget and time [3]. Terrain mapping using LiDAR and manned aircraft are very costly but has low ground resolution and limited time frame hence, rather impractical to be used for low altitude and small area surveying. Recently, UAV has been given a great attention in many applications including terrestrial terrain mapping, mainly, due to its low cost and practicality [10-11]. A UAV is commonly integrated with autopilot technology that enables semi or full autonomous navigation and image acquisition capabilities [1]. The image acquisition capabilities enable Earth terrain to be mapped and modelled to produce orthophoto. Orthophoto is an aerial photograph that has been geometrically rectified with appropriate scale and curvature, which has been considered as a vital element in the field of photogrammetry. Besides orthophoto, images acquired from UAV can also be used to generate Digital Terrain Model (DTM), which is the spatial terrain elevations of bare-earth, DTM can be utilized
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Securing Embedded Systems for Unmanned Aerial Vehicles

Securing Embedded Systems for Unmanned Aerial Vehicles

Countries around the globe have become increasingly reliant on unmanned aerial vehicles (UAVs). UAVs are extremely useful in many areas such as the military, civilian, and commercial fields and are a common tool to conduct search and rescue missions. These drones perform missions with high levels of complexity and are useful for cases where a human pilot would face certain risks. They require less human operator participation due to their autonomous behavior. In the case of emergency situations such as natural disasters, UAV systems can be programmed to complete missions from takeoff to landing. An example of this is shown in Figure 2 where a UAV is used to find missing hikers in a search and rescue mission. These missions include high navigation precision and long operation times that are tedious for human pilots. UAVs are also much cheaper, faster, and safer than using helicopters for search and rescue mission according to researchers [1]. Historically these drones were primarily used in defense operations but lately they have seen more use in the civilian world. UAVs wide ranges of missions are also used by the Air Force United States Marine Corps, Army, and Navy [2]. The National Defense UAVs represent a variety of missions and technology that range from large vehicles that carry offensive weapons to miniature systems whose components are light and compact to be carried in a
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Multi-agent pathfinding for unmanned aerial vehicles

Multi-agent pathfinding for unmanned aerial vehicles

Choosing a suitable mapf algorithm for the problem at hand is not always (in fact, almost never) straightforward. Many factors can influence this choice: density of agents, number of agents, map structure (defined as the density and layout of obstacles within a map), optimality requirements and speed requirements. There does not seem to be a definitive consensus on which algorithm to choose under different configurations of theses factors, creating an excellent area of future research. This lack of consensus also led to one of the questions being addressed in this thesis — “What is a good mapf algorithm for use with UAVs in wide open maps with few obstacle and a varying number of overlapping paths?”. One important factor that needs to be considered when answering this question is the differences between pathfinding in 2D and 3D space. On the one hand, hard mapf instances in 2D space will likely be easier to solve in 3D space, thanks to the extra dimension agents can occupy. On the other hand, this third dimension adds complexity to development and introduces more chances for bugs. With that said, finding conflict-free paths for UAVs is very important due to the dangers posed to humans with UAVs operating overhead. So even though many mapf problem instance will be solved easier in 3D space, the worst case (i.e. many densely operating agents) must be taken into account.
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Exploring Security Vulnerabilities of Unmanned Aerial Vehicles

Exploring Security Vulnerabilities of Unmanned Aerial Vehicles

We are currently observing a significant increase in popularity of Unmanned Aerial Vehicles (UAVs). This is not only the case for con- sumer UAVs, but also for more sophisticated UAVs used for profes- sional services, whereby the cost can easily be magnitudes higher. Given that professional UAVs are being widely deployed in sensitive missions such as monitoring of critical infrastructures and police op- erations, security aspects of such UAVs should be questioned. In this research we investigated the level of security applied to the commu- nication channels of a professional UAV. Furthermore, we explored security vulnerabilities that were identified, performed a Man-in-the- Middle attack and injected control commands to interact with the UAV. In addition, appropriate countermeasures to improve the cur- rent level of security were suggested. Our findings raise awareness within (i) the general public that use and trust UAVs, (ii) the scien- tific community by showing that further investigation is needed in this area, and (iii) the manufacturers by showing the importance of implementing a higher level of security in their devices.
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Unmanned Aerial Vehicles and the Future of Asset Management

Unmanned Aerial Vehicles and the Future of Asset Management

Comparatively in Canada, the growing market demand for UAV applications is estimated to be as large as $100 to $260 M from commercial operations over a 10-year period 7 . According to industry specialists, the top UAV applications to date support a variety of small to medium sized businesses such as agriculture, aerial imaging, construction, energy/oil, entertainment, infrastructure inspections and real estate. Transport Canada verifies this information, acknowledging how the regulatory agency is increasing permits yearly for commercial UAVs, which in the first quarter of 2015 permitted 67 operations certificates throughout BC (See Appendix D – Transport Canada UAV Background and Statistics). Considering this market uptake, UAVs offer technological advantages in (1) Asset inspections, (2) Video Marketing, (3) Aerial Surveying, (4) Delivery, and (5) Other. Table B below highlights the application of UAVs by market category.
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Design and Manufacturing of Pesticide Spraying Machine

Design and Manufacturing of Pesticide Spraying Machine

In order to reduce the harm to the environment and people the research and development of plant protecting machine focus on improving the mechanical work efficiency and the effective availability of pesticide. One of the most common forms of pesticides application, especially in conventional agriculture, is the use of mechanical sprayers. Hydraulic sprayers consist of a tank, a pump, a lance (for single nozzles) or boom, and a nozzle (or multiple nozzles). Sprayers convert a pesticide formulation, of one containing a mixture of water (or another liquid chemical carrier, such as fertilizer) and chemical, into droplets, which can be large rain-type drops or tiny almost invisible particles. This conversion is accomplished by forcing the spray mixture through a spray nozzle under pressure. The size of droplets can be altered through the use of different nozzle sizes, or by altering the pressure under which it is forced, or a combination of both. Large droplets have the advantage of being less susceptible to spray drift, but require more water per unit of land covered. Due to static electricity, small droplets are able to maximize contact with a target organism, but very still conditions are required. Sprayers are commonly used on farms to spray pesticides, herbicides, fungicides, and defoliants as a means of crop quality control.
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Game of Drones : Exploring the development of unmanned aerial vehicles in public safety organisations

Game of Drones : Exploring the development of unmanned aerial vehicles in public safety organisations

By analogy, a 'game of drones' is introduced in this study to illustrate the political and societal debate about uncertainties associated with drone-related technology. This study has explored a socio-technical playing field in which these discussions and the learning process of actors are important dynamics. In eight semi-structured interviews, nine respondents in Dutch national police and fire department were asked to present their views about technological performance, societal embedding and opportunities and challenges regarding the drone innovation. The results of this study have shown that actors are effectively and constructively working together to learn about the functionalities of drones - in relation to the attention drones receive in (international) media. In two experimental projects, actors are treating drones as an addition to the armoury, rather than replacing the existing surveillance devices. Drone implementation is furthermore carefully introduced in other parts of the organisation. In light of this study's results, it can be concluded that actors not only learning to work with drones, but are also investing in the relations in the maatschappelijk krachtenveld of drone development. Still, this study show that there are undesirable aspects in the learning process that affect the implementation of drones, such as: (1) an unscheduled extension of the projects; (2) a focus on solving practical issues rather than the uptake of drones in society; (3) not actively pursuing future opportunities of the drone technology; and (4) no direct state monitoring and evaluation. The results indicate that the experimental projects provide a lot of new information of and understanding about the use of drones. However, the problems encountered by the actors are often difficult to solve by the actors alone. Although the project actors are primarily focused on overcoming practical challenges, they do not contribute to the next step in the development of drones nor are they proactively adapting to their future functionalities.
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A Review on Geo Mapping with Unmanned Aerial Vehicles

A Review on Geo Mapping with Unmanned Aerial Vehicles

The design of flight paths is an important component of UAV mapping. This is typically done using software packages; many drone manufacturers offer proprietary software with their drones. Mission Planner, an open-source software package, is the single most widely used solution. The functionality of several competing software packages is broadly similar. UAV mapping missions are usually flown in a specific pattern of parallel lines, commonly described as “transects,” which are connected to a series of “waypoints”—think of a connect-the-dots pattern of parallel lines, or the pattern in which you might mow the lawn. A transect flight pattern is a method of ensuring that the UAV captures an adequate quantity of images that overlap to the degree required for the processing software to create a high-quality and accurate map. For maximum quality, some UAV mappers suggest flying two different overlapping patterns over the same area but at different heights. This method collects a large quantity of data and helps to resolve elevation variation problems, which result when tall geographic features throw off the scale of the rest of the image. Others recommend adjusting the altitude of the drone to keep a constant altitude above ground level, even as features on the ground vary in altitude. To create a flight plan with transects using current software such as Mission Planner, the pilot first connects with the UAV’s flight controller via either a ground control radio attached by USB cable to a computer or tablet, or a direct USB link from the UAV to the computer. (Flight plans can also be generated on the computer and uploaded to the flight controller later). The pilot opens the software and defines an area to be mapped with a polygon, then specifies the camera model, the desired operational altitude, and how the camera will be triggered to take photographs. Once these factors are entered, Mission Planner generates
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Verifiable control of a swarm of unmanned aerial vehicles

Verifiable control of a swarm of unmanned aerial vehicles

Therefore, the properties of the equilibrium state ρeq are shown in Table 1; Table 1: Stability of equilibrium states 2.3.1 ∂ 2 U/∂ρ2i Stability r >0 stable minimum r √ r+ µ √ r− µ 0 sta[r]

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Towards the development of 1-to-n human machine interfaces for unmanned aerial vehicles

Towards the development of 1-to-n human machine interfaces for unmanned aerial vehicles

Whilst these observed latencies might not seem suitable for real-time low-level command and control, the observed values are adequate for high-level interaction between vehicles and operators. For example, functions such as telemetry and vehicle state, waypoint and flight plan update, payload information, etc; are achievable within the current performance of the framework. During these experiments the focus was placed on the software side of the approach. However, by adopting a more thorough design of the network infrastructure the bandwidth and latency will greatly improve. The adoption hardware independent approaches such as the one proposed in this paper will be important for increasing performance of UAS operations, and also for reducing manpower needed for UAS missions.
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Vision-based Absolute Localization for Unmanned Aerial Vehicles

Vision-based Absolute Localization for Unmanned Aerial Vehicles

Initially introduced by the US Army during World War I (1917), UAVs were, for a long time, considered both very unreliable and inaccurate in term of maneuverability and nav- igation capabilities. Mostly used for military tasks claimed to be too risky or dangerous for humans, they were referred as the "Eyes of the Army" [19]. Today, they have reached such a level of sophistication that their usage and appli- cation have become a real technological challenge. Wide and expanding, UAVs applications are commonly associated with exploration, inspection or surveillance tasks. A deciding factor for the success of these tasks is the localization or navigation capability of the drone. Unfortunately, this can be particularly difficult when dealing with low-quality Inertial Measurement Unit (IMU), Global Positioning System (GPS), or when flying in bad weather conditions (which decreases the quality of the GPS navigation). Even though some approaches for robust Inertial/GPS localization have been studied [18], lack of precision and signal interferences still have to be considered. An alternative to avoid these problems is to mount a vision system on the UAV which can provide a temporary alternative to IMU/GPS navigation unit.
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Analysis of Model-Aided Navigation of Unmanned Aerial Vehicles

Analysis of Model-Aided Navigation of Unmanned Aerial Vehicles

experimental quadcopter application in which they demonstrated that even though no rotational vehicle dynamics are modeled (they use only translational dynamics modeling), roll angles, pitch angles and even IMU biases with bounded errors are estimable with model-aided navigation. Further, for fixed wing aircraft, Bryson and Sukkarieh[ 4 ], considered using a VDM to predict the aircraft state vector which are then fused with the IMU measurements via an Extended Kalman filter to estimate the errors in the inertial sensors and in the VDM computations. In this work, they showed that the simulation results related to the different INS configurations considered improves the navigation system performance even when small parameter errors are present in the model. Further, it is shown that IMU bias estimation depends mainly on sudden acceleration errors in the VDM and also on growing errors in the VDM velocity and Euler angles. More recently Cappello et. al [ 5 ] combines VDM, called Aircraft Dynamics Models (ADM), with Global Navigation Satellite System (GNSS), Micro-Electromechanical System based Inertial Measurement Unit (MEMS-IMU) and Vision-Based Navigation (VBN) sensors and relative different combinations of them in order estimate position, velocity and attitude for the Aerosonde RPAS UAV also in the context of precision approach and landing phases. Khaghani and Skaloud [ 6 ] use a conventional INS/GNSS setup where position, velocity, and attitude are estimated using a VDM and an EKF considering at the same time wind and GNSS outages too.
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Vision-Based navigation system for unmanned aerial vehicles

Vision-Based navigation system for unmanned aerial vehicles

navigation and obstacle detection and avoidance in the last decade. The advan- tages and improvements of computer vision algorithms towards the presented reli- able solutions have been presented through real results under demanding circum- stances, such as, pose estimation or aerial obstacle avoidance. So, complex tasks and applications have been analyzed and difficulties have been highlighted, where the trustable performance of the vision-based solutions and the improvements in relation to the previous works of the literature are provided.

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Observing river stages using unmanned aerial vehicles

Observing river stages using unmanned aerial vehicles

It is also important to discuss limitations, which may con- strain extrapolation of the results to other rivers. Channel morphology, mainly the slope of banks, may have a signif- icant impact on the observation of water surface area with the UAV. Therefore, the results prepared for a specific river in the SW Poland are not transferable to other rivers with differ- ent cross-sectional parameters. Indeed, Smith (1997) argues that “Until additional empirical rating curves relating inun- dation area to ground measurements of stage or discharge are made, it is difficult to assess their potential for extrap- olation to other rivers of similar morphology. However, it seems likely that such curves will vary significantly between rivers and therefore must be constructed for each site”. How- ever, our approach focuses mainly on a statistical analysis of water surface areas, not river stages themselves. In fact, we quantitatively infer on statistically meaningful changes in water surface area (this is a key part of our procedure) and only qualitatively, through the existence of a relation- ship between water surface areas and river stages published by Usachev (1983), extrapolate our results into changes in river stages. We believe that our quantitative approach (re- call that this concerns seeking changes in water surface areas in the orthophotomaps produced from the UAV-taken pho- tographs) forms a general method that – under several condi- tions clearly identified in the manuscript – may be applied in other regions. However, the use of the approach to infer on river stages should be made with caution, since such an ex- trapolation requires a knowledge about the relationship be- tween water surface areas and river stages (and the charac- teristics of this relation are vulnerable to sites-specific river morphology, especially bank slopes).
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