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The purpose of this study is to offer a better and more effective hexacopter design for a 3 kg payload using finite element analysis (FEA), facilitating the use of different materials for different components that too without compromising strength.

A 3D computer-aided design (CAD) model of a hexacopter with a regular hexagonal frame is presented. Furthermore, a finite element model is developed to perform a structural analysis and determine Von Mises stress and strain values along with deformations of different components of the proposed hexacopter design.

The results establish that carbon fibre outperforms acrylonitrile butadiene (ABS) with respect to deformations. Within the permissible limits of the stress and strain values, both carbon fiber and ABS are suggested for different components. Thus, a proposed hexacopter offers lighter weight, high strength and low cost.

The use of different materials for different components is suggested by making use of static structural analysis. This encourages new research work and helps in developing new applications of hexacopter, and it has never been reported in literature. The suggested materials for the components of the hexacopter will prove to be suitable considering weight, strength and cost.

This study aims to minimize the risk of costly failures of flight tests during the path tracking control design, and a noble approach has been proposed in this study to put the whole vehicle-in-the simulation loop. Working with the real system is essential for developing intelligent and data-driven controllers for multirotor drones which needs learning the drones' nonlinear complicated dynamics. The vehicle-in-the-loop (VIL) platform developed in this paper is a safe and effective solution to deal with this problem.

To avoid risky flight test during controller design, the multirotor is hinged to a shaft that allows the multirotor's angular motion but restricts translational motion. The test-bed includes the real system attitude dynamics and the simulation of the position dynamics to model the complete flight based on real-time reactions of the vehicle. For the authors' case study, a hexacopter angular motion provides the real-time attitude data in translational motion simulation loop. To test the set-up, a proportional-integral-derivative (PID) and a brain emotional learning-based intelligent controller (BELBIC) is implemented for tracking of circle and 8-shape flight trajectories.

The results show that the platform helps the intelligent controller to learn the system dynamics without worrying about the failure in the early stages of the design and in the real-world flight test. Although the hexacopter translational dynamics is modeled in simulation, the authors still have highly accurate attitude dynamics matching the requirement of the control loop design. The comparison of the two controllers also shows that the performance of BELBIC is better than PID in this test.

The research background is reviewed in the introduction section. The other sections are originally developed in this paper.

This study aims to test a multirotor unmanned aerial vehicle (UAV) paired with a thermal imaging camera for detecting big game species such as Eurasian elk, red deer, European roe deer and Eurasian wild boar.

The research work was carried out in the Czarna Bialostocka Forest District (Podlaskie Voivodeship, Poland). A thermal imaging camera E20Tvx Yuneec with a view angle of 33° × 26.6° and a thermal sensor resolution of 640 × 512 pixels was selected for the research. The Yuneec H520E hexacopter was chosen as the lifting vehicle. The flights for the study were conducted between the autumn of 2021 and the winter of 2022. The UAV was flown at two different altitudes, 120 and 80 m above ground level, which provided a ground sampling distance of 11 and 7 cm, respectively.

The results so far have shown the potential of commercially available thermal imaging cameras for detecting and identifying big game species, such as Eurasian elk and red deer. Moreover, in the winter season of 2022 on the 7th and 13th of March, it was also possible to determine the sex of red deer distinguishing between males and females. The results of the survey made with the thermal camera were compared to the assessment from the standard method for the determination of the game population in the Czarna Bialostocka sub-district. In the case of red deer, the results of the research carried out during the winter exceed five times the numbers obtained as a result of the traditional inventory. That is most likely due to the gregarious occurrence of this species in the winter season.

The use of thermovision to estimate the population and sex of animals is a relatively new issue, especially in Poland, where the use of thermal imaging is not the official method of research of big game species yet.

Nowadays, food problems are likely to arise because of the increasing global population and decreasing arable land. Therefore, it is necessary to increase the yield of agricultural products. Pesticides can be used to improve agricultural land products. This study aims to make the spraying of cherry trees more effective and efficient with the designed artificial intelligence (AI)-based agricultural unmanned aerial vehicle (UAV).

Two approaches have been adopted for the AI-based detection of cherry trees: In approach 1, YOLOv5, YOLOv7 and YOLOv8 models are trained with 70, 100 and 150 epochs. In Approach 2, a new method is proposed to improve the performance metrics obtained in Approach 1. Gaussian, wavelet transform (WT) and Histogram Equalization (HE) preprocessing techniques were applied to the generated data set in Approach 2. The best-performing models in Approach 1 and Approach 2 were used in the real-time test application with the developed agricultural UAV.

In Approach 1, the best F1 score was 98% in 100 epochs with the YOLOv5s model. In Approach 2, the best F1 score and mAP values were obtained as 98.6% and 98.9% in 150 epochs, with the YOLOv5m model with an improvement of 0.6% in the F1 score. In real-time tests, the AI-based spraying drone system detected and sprayed cherry trees with an accuracy of 66% in Approach 1 and 77% in Approach 2. It was revealed that the use of pesticides could be reduced by 53% and the energy consumption of the spraying system by 47%.

An original data set was created by designing an agricultural drone to detect and spray cherry trees using AI. YOLOv5, YOLOv7 and YOLOv8 models were used to detect and classify cherry trees. The results of the performance metrics of the models are compared. In Approach 2, a method including HE, Gaussian and WT is proposed, and the performance metrics are improved. The effect of the proposed method in a real-time experimental application is thoroughly analyzed.

The purpose of this paper is to deal with the study of an innovative unmanned mission to Mars, which is aimed at acquiring a great amount of detailed data related to both Mars’ atmosphere and surface.

The Mars surface exploration is conceived by means of a fleet of drones flying among a set of reference points (acting also as entry capsules and charging stations) on the surface. The three key enabling technologies of the proposed mission are the use of small satellites (used in constellation with a minimum of three), the use of electric propulsion systems for the interplanetary transfer (to reduce the propellant mass fraction) and lightweight, efficient, drones designed to operate in the harsh Mars environment and with its tiny atmosphere.

The low-thrust Earth-Mars transfer is designed by means of an optimization approach resulting in a duration of slightly more than 27 months with a propellant amount of about 125 kg, which is compatible with the choice of considering a 500 kg-class spacecraft. Four candidate drone configurations have been selected as the result of a sensitivity analysis. Flight endurance, weight and drone size have been considered as the driving design parameters for the selection of the final configuration, which is characterized by six rotors, a total mass of about 6.5 kg and a flight endurance of 28 minutes. In the mission scenario proposed, the drone is assumed to be delivered on the Mars surface by means of a passive entry capsule, which acts also as a docking station and charging base. Such a capsule has been sized both in terms of mass (68 kg) and power (80 W), showing to be compatible with 500 kg-class spacecraft.

As a general conclusion, the study shows the mission concept feasibility.

The concept would return incomparable scientific data and can be also be potentially implemented with a relatively low budget exploiting of the shelf components to the larger extent, small identical spacecraft buses and modular low-cost drones.

The innovative mission architecture proposed in this study aims at providing a complete coverage of the surface and lowest atmospheric layers. The main innovation factor of the proposed mission consists in the adoption of small multi-copter UAVs, also called “drones,” as remote-sensing platforms.

This paper aims to illustrate the growing role of drones in applications involving physical tasks.

Following a short introduction, this first provides a brief introduction to drone technology. It then describes and discusses products and applications involving physical tasks in agricultural and forestry, maritime rescue, firefighting and product delivery. Finally, brief conclusions are drawn.

Excluding military applications, drones were initially used primarily for image acquisition. Numerous different designs have since been developed with greatly varying wing configurations, payloads, flight duration, power sources and other features which are increasingly being used to conduct physical tasks. In the applications considered here drones are applying agrochemicals and dispersing crop and tree seeds; saving lives by deploying lifeboats and buoyancy aids; extinguishing fires in high-rise buildings and forests; and delivering groceries, food, mail, medicines and humanitarian aid, often in and to remote locations.

This study provides a detailed insight into selection of applications in which drones conduct physical tasks.

Estimating the pose – position and orientation – of a moving object such as a robot is a necessary task for many applications, e.g., robot navigation control, environment mapping, and medical applications such as robotic surgery. The purpose of this paper is to introduce a novel method to fuse the information from several available sensors in order to improve the estimated pose from any individual sensor and calculate a more accurate pose for the moving platform.

Pose estimation is usually done by collecting the data obtained from several sensors mounted on the object/platform and fusing the acquired information. Assuming that the robot is moving in a three-dimensional (3D) world, its location is completely defined by six degrees of freedom (6DOF): three angles and three position coordinates. Some 3D sensors, such as IMUs and cameras, have been widely used for 3D localization. Yet, there are other sensors, like 2D Light Detection And Ranging (LiDAR), which can give a very precise estimation in a 2D plane but they are not employed for 3D estimation since the sensor is unable to obtain the full 6DOF. However, in some applications there is a considerable amount of time in which the robot is almost moving on a plane during the time interval between two sensor readings; e.g., a ground vehicle moving on a flat surface or a drone flying at an almost constant altitude to collect visual data. In this paper a novel method using a “fuzzy inference system” is proposed that employs a 2D LiDAR in a 3D localization algorithm in order to improve the pose estimation accuracy.

The method determines the trajectory of the robot and the sensor reliability between two readings and based on this information defines the weight of the 2D sensor in the final fused pose by adjusting “extended Kalman filter” parameters. Simulation and real world experiments show that the pose estimation error can be significantly decreased using the proposed method.

To the best of the authors’ knowledge this is the first time that a 2D LiDAR has been employed to improve the 3D pose estimation in an unknown environment without any previous knowledge. Simulation and real world experiments show that the pose estimation error can be significantly decreased using the proposed method.

This paper aims to discuss search and rescue (SAR) and disaster relief robot developments, trials and applications and to answer the question posed in the title.

Following a short introduction, this first describes Integrated Components for Assisted Rescue and Unmanned Search operations, a recent, collaborative, European research project, and euRathlon, a major robotics competition. It then highlights the role of the centre for robot-assisted search and rescue, and provides examples of the deployment of terrestrial, marine and airborne robots in real SAR and disaster relief situations. It concludes with a brief discussion.

This shows that SAR and disaster relief robots are the topic of an extensive development effort, and many have performed well in simulated disaster scenarios. Terrestrial, marine and airborne robots have been used in many real disaster relief situations since 2001, and the use of unmanned aerial vehicles has proliferated due to recent technological developments. Robots now play an important role in supporting SAR teams, and this will certainly increase as the technologies are developed further.

In an era characterized by extreme weather events and continuing military conflicts, robots play an increasingly important role in supporting human disaster response teams. This article provides details of developments, trials and real-world deployments of such robots.

The motivation to perform research on feedback control system for unmanned aerial vehicles, a fact that each quadrocopter is unstable.

For this reason, it is necessary to design a control system which is capable of making unmanned aerial vehicle vertical take-off and landing (UAV VTOL) stable and controllable. For this purpose, it was decided to use a feedback control system with cascaded PID controller. The main reason for using it was that PID controllers are simple to implement and do not use much hardware resources. Moreover, cascaded control systems allow to control object response using more parameters than in a standard PID control. STM32 microcontrollers were used to make a real control system. The rapid prototyping using Embedded Coder Toolbox, FreeRTOS and STM32 CubeMX was conducted to design the algorithm of the feedback control system with cascaded PID controller for unmanned aerial vehicle vertical take-off and landings (UAV VTOLs).

During research, an algorithm of UAV VTOL control using the feedback control system with cascaded PID controller was designed. Tests were performed for the designed algorithm in the model simulation in Matlab/Simulink and in the real conditions.

It has been proved that an additional control loop must have a full PID controller. Moreover, a new library is presented for STM32 microcontrollers made using the Embedded Coder Toolbox just for the research. This library enabled to use rapid prototyping while developing the control algorithms.

The purpose of this paper hinged on the concept of smart libraries and their development for the furtherance of information access, dissemination and information resources and services delivery in Caribbean libraries.

To conduct this research, the literature of smart libraries and technologically driven and their application in libraries were reviewed by examining existing literature on information and communication technologies and technology in libraries.

The literature highlighted that this technological advancement is not yet fully on stream in academic libraries of the Caribbean owing to the lack of financial, technological and organizational resources. It further outlined that certain aspects of library automation are fostered through the inclusion of technology.

The limitation of this study is that only academic libraries of the Caribbean region were assessed. Other regions should be explored in future research.

The concept of smart libraries is an emerging issue with limited scope for scrutiny; a systematic and extensive review of recent research on smart in libraries is unavailable. This paper presents an overview of smart libraries or technologically driven libraries, its findings for potential research opportunities and development for academic libraries. In addition, it will build on the body of knowledge that is presently non-existent on smart libraries in the Caribbean.