Aerial Robotic System Research Articles

Prospects for the use of modern interactive technologies in the process of training police officers for activities under martial law

The article analyses the possibilities of using modern technologies in the tactical and specialised training of police officers under martial law. Martial law creates emergency situations when police officers have to work in conditions of increased danger and instability. In such circumstances, the use of modern technologies in tactical and specialised training of police officers becomes extremely important in order to ensure their safety, efficiency and success in performing their tasks. The article outlines the benefits of using technologies such as virtual reality, augmented reality, unmanned aerial vehicles, robotic systems and artificial intelligence. Thus, the main areas of application of modern technologies in the tactical and special training of police officers are: the use of virtual reality and augmented reality to develop practical skills, in particular for training in combat operations, which ensures more effective training of police officers; the use of unmanned aerial vehicles to monitor and obtain information about the situation on the ground without risking the lives of police officers; the use of robotic systems to perform dangerous or difficult tasks, in particular tasks of search and rescue; the use of virtual reality and augmented reality to develop practical skills, in particular for training in combat operations, which ensures more effective training of police officers; the use of virtual reality and augmented reality to develop practical skills, in particular for training in combat operations, which ensures more effective training of police officers. It is noted that the use of modern technologies can increase the effectiveness of police training, reduce the risk to their lives and improve the safety of citizens. The author concludes that the use of modern technologies is an integral part of the tactical and specialised training of police officers under martial law. Technology helps police officers to effectively counter threats, provide security and be successful in their work. The development and improvement of these technologies is an important area for improving the effectiveness of police work under martial law. The introduction of modern technologies in tactical and specialised training of police officers is an important task that will increase the effectiveness of police activities under martial law.

Adaptive Nonsingular Fast-Reaching Terminal Sliding Mode Control Based on Observer for Aerial Robots

In this article, an observer-based adaptive non-singular fast-reaching terminal sliding mode control strategy is proposed to tackle the problem of actuator faults and uncertain disturbance in aerial robot systems. Firstly, a model of an aerial robot system is established through dynamic analysis. Next, an adaptive observer, combined with a fast adaptive fault estimation (FAFE) algorithm, is proposed to estimate system states and actuator failure and compensate for faults in a precise and prompt manner. In addition, a non-singular fast terminal sliding surface is defined, taking into account the fast convergence of the tracking errors in order to provide appropriate trajectory tracking results. Since the upper bounds of the disturbances caused by the manipulator of the system in practice are unknown, the control approach may benefit from the addition of an adaptive control strategy that can suppress the influence of uncertain disturbances. The Lyapunov stability theory demonstrates that tracking errors are able to converge stably and quickly. In the end, the contrast experiment is conducted to exhibit the effectiveness of the proposed control strategy. The results demonstrate quicker convergence and improved estimating accuracy.

Developing and Field Testing Path Planning for Robotic Aquaculture Water Quality Monitoring

Marine food chains are highly stressed by aggressive fishing practices and environmental damage. Aquaculture has increasingly become a source of seafood which spares the deleterious impact on wild fisheries. However, continually monitoring water quality to successfully grow and harvest fish is labor intensive. The Hybrid Aerial Underwater Robotic System (HAUCS) is an Internet of Things (IoT) framework for aquaculture farms to relieve the farm operators of one of the most labor-intensive and time-consuming farm operations: water quality monitoring. To this end, HAUCS employs a swarm of unmanned aerial vehicles (UAVs) or drones integrated with underwater measurement devices to collect the in situ water quality data from aquaculture ponds. A critical aspect in HAUCS is to develop an effective path planning algorithm to be able to sample all the ponds on the farm with minimal resources (i.e., the number of UAVs and the power consumption of each UAV). Three methods of path planning for the UAVs are tested, a Graph Attention Model (GAM), the Google Linear Optimization Package (GLOP) and our proposed solution, the HAUCS Path Planning Algorithm (HPP). The designs of these path planning algorithms are discussed, and a simulator is developed to evaluate these methods’ performance. The algorithms are also experimentally validated at Southern Illinois University’s Aquaculture Research Center to demonstrate the feasibility of HAUCS. Based on the simulations and experimental studies, HPP is particularly suited for large farms, while GLOP or GAM is more suited to small or medium-sized farms.

Transient bio-inspired gliders with embodied humidity responsive actuators for environmental sensing.

Collecting temporal and spatial high-resolution environmental data can guide studies in environmental sciences to gain insights in ecological processes. The utilization of automated robotic systems to collect these types of data can maximize accuracy, resilience, and deployment rate. Furthermore, it reduces the risk to researchers deploying sensors in inaccessible environments and can significantly increase the cost-effectiveness of such studies. The introduction of transient robotic systems featuring embodied environmental sensors pushes towards building a digital ecology, while introducing only minimal disturbance to the environment. Transient robots made from fully biodegradable and non-fossil based materials, do not develop into hazardous e-waste at the end of their lifetime and can thus enable a broader adoption for environmental sensing in the real world. In this work, our approach towards the design of transient robots includes the integration of humidity-responsive materials in a glider, which is inspired by the Alsomitra macrocarpa seed. The design space of these gliders is explored and their behavior studied numerically, which allows us to make predictions on their flight characteristics. Results are validated against experiments, which show two different gliding behaviors, that can help improve the spread of the sensors. By tailoring the Cellulose-Gelatin composition of the humidity actuator, self-folding systems for selective rainwater exposure can be designed. The pH sensing layer, protected by the actuator, provides visual feedback on the pH of the rainwater. The presented methods can guide further concepts developing transient aerial robotic systems for sustainable, environmental monitoring.

Trajectory Planning of Aerial Robotic Manipulator Using Hybrid Particle Swarm Optimization

The trajectory planning of an aerial robotic manipulator system is studied using Hybrid Particle Swarm Optimization (HPSO). The aerial robotic manipulator is composed of an unmanned aerial vehicle (UAV) base and a robotic manipulator. The robotic manipulator is dynamically singular. In addition, strong coupling exists between the UAV base and the robotic manipulator. To overcome the problems, the trajectory planning is studied in the join space using HPSO. HPSO combines superiorities of PSO and GA (Genetic Algorithm), prohibiting particles from becoming trapped in a local minimum. In addition, the control parameters are self-adaptive and contribute to fast searching for the global optimum. The trajectory planning problem is converted into a parameter optimization problem. Each joint trajectory is parameterized with a Bézier curve. The HPSO is implemented to optimize joint trajectories, satisfying specific objectives and imposed constraints. Numerical simulations are also carried out to validate the effectiveness of the proposed method.

Low-Complexity Prescribed Performance Control for Unmanned Aerial Manipulator Robot System Under Model Uncertainty and Unknown Disturbances

This article presents a trajectory tracking control method for the unmanned aerial manipulator robot system (UAMRS) under model uncertainty and unknown disturbances. More specifically, a low-complexity prescribed performance controller is proposed to effectively reduce the design complexity and achieve the prescribed transient and steady-state performance. First, the dynamics model of the UAMRS is analyzed and modeled, where the unmeasured internal interaction generated by the coupling effect and the random environmental disturbances are considered simultaneously. Then, utilizing the property of prescribed performance, the UAMRS with model uncertainty and external disturbances can guarantee preferable trajectory tracking responses, where the nonlinear disturbance observer is used to estimate and compensate uncertainties and external disturbances. Moreover, the proposed controller defined by simple expressions does not require accurate knowledge of the UAMRS, which is of low complexity and can effectively reduce the amount of calculation. The stability of the proposed controller is analyzed. Finally, the performances of the proposed scheme are demonstrated by the numerical simulation comparisons and real-world experiments, where a quadrotor with a 3-DOF onboard active manipulator is adopted in outdoor experimental validations.

PHILOSOPHICAL ANALYSIS OF THE MILITARY‐TECHNICAL REVOLUTION OF THE XXI CENTURY

At the beginning of the XXI century the term military‐technical revolution (MTR) was increasingly used. The article presents its philosophical analysis and the history of its appearance, gives main features of revolutions, substantiates their number relying on analytical research in the field of hilosophy of society and in the field of philosophy of war, both domestic and foreign experts. The connection between revolution and technical and technological structure of society, on the one hand, and changes in the nature of modern warfare, terms and scale of the development of hostilities, on the other, is shown. Proceeding from traditional philosophical thoughts on philosophy of technology, author focused on transformations characteristic of modern warfare, the importance of ontological and anthropological factors in modern military affairs. Author relies on a wide illustrative material that made it possible to show changes in the sixth military‐technical revolution. As an example (a kind of Case study method), author examines nature of the use of unmanned aerial vehicles and robotic military systems in modern warfare. Based on specific material, author proves that the character of modern warfare is hybrid in nature, but hybridity itself is heterogeneous in nature. The latter made it possible to assert the existence of a transitional period between the sixth and the seventh military‐technical revolutions.

Decentralised aerial swarm for adaptive and energy efficient transport of unknown loads

• We present a behaviour based subsumption architecture that enables a swarm’s topology to adapt to a load's mass distribution. • The decentralized self-organized swarm can perform a cooperative load transportation task without any explicit communication between members. • Our architecture has the potential to be scalable to a large number of agents. • This is significant in aerial swarm cooperative transport systems because it leads to even energy distribution among swarm members when compared to a uniform swarm topology. • It also fosters robustness of the load-suspended aerial robot system. Cooperative transport by a swarm of Quadcopters offers more flexibility and performance when carrying loads that are complex in structural profile and mass. Ensuring that team members of the swarm are optimally placed on these loads as well as able to resist disturbances from the environment during transport are current research challenges. In this paper, we present a decentralized behaviour based subsumption architecture for enabling a swarm of Quadcopters to explore an unfamiliar area, find a load and transport it to a target location cooperatively. In the architecture, three behaviours were used: an obstacle avoidance behaviour to avoid collisions with objects in the environment, a flocking behaviour to ensure swarm structure and a bacterium behaviour for exploration of the environment and to adapt to the mass profile of various detected loads. By adapting to the mass profile of a detected load, we show that our architecture ensures even energy distribution among Quadcopters while achieving robustness to disturbances from the environment. Our results show that a mass adapting swarm is able to conserve energy during payload transportation when compared to a swarm that does not adapt to a load’s profile. Furthermore, we do not use explicit communication between team members but instead rely on data from visual sensors attached to the Quadcopters. We experiment with simulations in a physics informed robot simulator called CoppeliaSim and demonstrate the effectiveness of our architecture when utilized for cooperative transport of irregular loads.

Pulse Width Modulation Analysis of Five-Level Inverter- Fed Permanent Magnet Synchronous Motors for Electric Vehicle Applications

In recent times, intense research has been focused on the performance enhancement of permanent magnet synchronous motors (PMSM) for electric vehicle (EV) applications to reduce their torque and current ripples. Permanent magnet synchronous motors are widely used in electric vehicle systems due to their high efficiency and high torque density. To have a good dynamic and transient response, an appropriate inverter topology is required. In this paper, a five-level inverter fed PMSM for electric vehicle applications, realized via co-simulation in an electromagnetic suite environment with a reduced stator winding current of PMSM via the use of in-phase disposition (PD) pulse width modulation (PWM) techniques as the control strategy is presented. The proposed topology minimizes the total harmonic distortion (THD) in the inverter circuit and the motor fed and also improves the torque ripples and the steady-state flux when compared to conventional PWM techniques. A good dynamic response was achieved with less than 10A stator winding current, zero percent overshoot, and 0.02 second settling time synchronization. Thus, the stator currents are relatively low when compared to the conventional PWM. This topology contribution to the open problem of evolving strategies that can enhance the performance of electric drive systems used in unmanned aerial vehicles (UAV), mechatronics, and robotic systems.

Safe Documentation of Historical Monuments by an Autonomous Unmanned Aerial Vehicle

The use of robotic systems, especially multi-rotor aerial vehicles, in the documentation of historical buildings and cultural heritage monuments has become common in recent years. However, the teleoperated robotic systems have significant limitations encouraging the ongoing development of autonomous unmanned aerial vehicles (UAVs). The autonomous robotic platforms provide a more accurate and safe measurement in distant and difficult to access areas than their teleoperated counterpart. Through the use of autonomous aerial robotic systems, access to such places by humans and building of external infrastructures like scaffolding for documentation purposes is no longer necessary. In this work, we aim to present a novel autonomous unmanned aerial vehicle designed for the documentation of hardly attainable areas of historical buildings. The prototype of this robot was tested in several historical monuments comprising scanned objects located in dark and hardly accessible areas in the upper parts of tall naves. This manuscript presents the results from two specific places: the Church of St. Anne and St. Jacob the Great in Stará Voda, and St. Maurice Church in Olomouc, both in the Czech Republic. Finally, we also compare the three-dimensional map obtained with the measurements made by the 3D laser scanner carried onboard UAV against the ones performed by a 3D terrestrial laser scanner.

A Mixed-Initiative Formation Control Strategy for Multiple Quadrotors

In this paper, we present a mixed-initiative motion control strategy for multiple quadrotor aerial vehicles. The proposed approach incorporates formation specifications and motion-planning commands as well as inputs by a human operator. More specifically, we consider a leader–follower aerial robotic system, which autonomously attains a specific geometrical formation, by regulating the distances among neighboring agents while avoiding inter-robot collisions. The desired formation is realized by a decentralized prescribed performance control strategy, resulting in a low computational complexity implementation with guaranteed robustness and accurate formation establishment. The multi-robot system is safely guided towards goal configurations, by employing a properly defined navigation function that provides appropriate motion commands to the leading vehicle, which is the only one that has knowledge of the workspace and the goal configurations. Additionally, the overall framework incorporates human commands that dictate the motion of the leader via a teleoperation interface. The resulting mixed-initiative control system has analytically guaranteed stability and convergence properties. A realistic simulation study, considering a team of five quadrotors operating in a cluttered environment, was carried out to demonstrate the performance of the proposed strategy.

Dynamical analysis and validation of motion control by filtering performance for aerial robotic system

Although drone appears in different applications, such as environmental inspection, agriculture or transportation, some aspects require more studies to clarify the efficient outcomes. One of them is to investigate the filtering performance such as Kalman and Complementary filters when the autonomous aerial system (AAS) handles its mission. However, it lacks the systematic research about these filters to provide the proper evaluation. Therefore, in this paper, the research topic related to AAS model to indicate the filtering effects in the agricultural application for making an alternative solution is presented. Firstly, the mathematical representation of system model is established in order to describe the dynamical performance and motion constraints. Then, the theory of filter structure is implemented to estimate the system state. The proposed design is validated in both numerical simulation and experiments. The system parameters that are monitored, include angular values of roll, pitch and yaw in three axes, motion parameters and its trajectories. By utilizing various sensing devices such as gyroscope, accelerometer and compass in real-world hardware, the experimental results could evaluate more precise and efficient design. The findings of this study are to (1) propose the model of AAS and proper filters, (2) launch the verified process and calibration, and (3) demonstrate the competitive performance among filters. From these results of our work, it could be clearly seen that the AAS plays an important role in daily applications and the related topics are still attractive.

Aerial Robots for Contact-Based Ultrasonic Thickness Measurements for Field Inspections

Aerial robotic systems, also referred to as drones, enable the collection of data on a scale and scope heretofore unimaginable. Field inspections at industrial sites using an aerial robotic inspection system that makes physical contact with a structure or asset as part of a nondestructive testing (NDT) or nondestructive evaluation (NDE) routine is safer than placing humans at elevation and enables more data to be gathered in less time. These aerial robotic systems are highly extensible and agile enabling safer, faster, and better inspections. Robotic inspection systems are forecast to grow exponentially this decade and beyond, as asset owners and service providers realize their economic value creation, increased data collection, and safety contributions.

Introducing autonomous aerial robots in industrial manufacturing

Although ground robots have been successfully used for many years in manufacturing, the capability of aerial robots to agilely navigate in the often sparse and static upper part of factories makes them suitable for performing tasks of interest in many industrial sectors. This paper presents the design, development, and validation of a fully autonomous aerial robotic system for manufacturing industries. It includes modules for accurate pose estimation without using a Global Navigation Satellite System (GNSS), autonomous navigation, radio-based localization, and obstacle avoidance, among others, providing a fully onboard solution capable of autonomously performing complex tasks in dynamic indoor environments in which all necessary sensors, electronics, and processing are on the robot. It was developed to fulfill two use cases relevant in many industries: light object logistics and missing tool search. The presented robotic system, functionalities, and use cases have been extensively validated with Technology Readiness Level 7 (TRL-7) in the Centro Bahía de Cádiz (CBC) Airbus D&S factory in fully working conditions.

An Intelligent Auto-Organizing Aerial Robotic Sensor Network System for Urban Surveillance

We have developed and demonstrated an intelligent auto-organizing aerial robotic sensor network system composed of cameras installed on UAVs and ground fixtures for urban surveillance using the decentralised control paradigm. The system can auto-organize to meet user requirements, changes to user requirements and when new UAVs or ground cameras are added or are lost due to failure. User designated targets can be automatically tracked and handed over from one camera to another, to ensure continuous tracking. The cameras can also self adjust their positions and pointing angles to cooperatively cover areas of interest completely. We have achieved this by designing a software architecture for managing multiple interacting algorithms online and in parallel, facilitating incremental software development and debugging. We have adapted algorithms to become computationally efficient and effective for real world use online and on-board the UAVs, and ensured that the integration of video analytics and tactical behaviours work in real world settings. We have also achieved near optimal, online close coordination of the UAVs and ground cameras. To the best of our knowledge, this is the first proof-of-concept of a fully integrated intelligent auto-organizing aerial robotic sensor network system of cameras installed on UAVs and ground fixtures for urban surveillance.

An aerial robotic system for inventory of stockpile warehouses

AbstractThis article describes the development and evaluation of an aerial robotic system for smart inventory of stockpile warehouses. The system was developed to automatically measure piles of different bulk materials, such as phosphorus and potassium compounds, which are stored in bays of different sizes inside a warehouse. This warehouse configuration is very common among fertilizer and animal food industries in Brazil. While an inventory can be executed by a human technician, the insalubrious environment, the imprecision of the manual volume estimation, and the time spent by the technician to access the information motivate the automation of the process. The proposed system uses a multirotor electrical drone that navigates autonomously inside the warehouse while it acquires light detection and ranging (LIDAR) point cloud data. This data is used to build a three‐dimensional (3D) model of the environment, which is then processed to identify the stockpiles of material and calculate their volumes. Since the environment is GPS‐denied and its characteristics, including symmetry, illumination and texture, do not favor visual‐ or LIDAR‐based localization, a drone navigation strategy that relies on relative positioning with respect to simple structures of the warehouse was developed. This article also presents our approach for autonomous stockpile volume estimation, which was numerically evaluated both in simulation and with real data, yielding in accuracy and precision of about 98%. The results presented in the article show that the aerial system is able to substitute the previously adopted manual procedure, highly increasing its accuracy, repeatably and safety, and drastically reducing its time of execution and cost.

Design and Control of a Deformable Trees-Pruning Aerial Robot

Tree branches near the electric power transmission lines are of great threat to the electricity supply. Nowadays, the tasks of clearing threatening tree branches are still mostly operated by hand and simple tools. Traditional structures of the multirotor aerial robot have the problem of fixed structure and limited performance, which affects the stability and efficiency of pruning operation. In this article, in order to obtain better environmental adaptability, an active deformable trees-pruning aerial robot is presented. The deformation of the aerial robot is implemented through two ways, arm telescopic and folding. In order to suppress the influence of internal and external disturbances on the system, Active Disturbance Rejection Control (ADRC) technology is adopted to build the flight controller. Firstly, active deformation aerial robot structure is given, followed by system dynamic model establishment under wind disturbance using the Newton–Euler method. Also, the analysis of the gusts influence on the system is considered. Then, the active deformation aerial robot system is decoupled into a combination of six SISO systems, so that a disturbance rejection controller is designed. Finally, the expanded state observer and the nonlinear state error feedback law are used to inspect and compensate the disturbance. Simulation results of attitude and position tracking as well as the antidisturbance capability show that the active deformation aerial robot with the ADRC flight controller designed in this paper has excellent attitude control capabilities during flight and trees-pruning operation.

Study on Arbitrary Direction Navigation System for Autonomous Multirotor with Arbitrary Configuration of Rotors

In this paper, an autonomous aerial robot system with a multirotor mechanism is described, where the robot has an arbitrary configuration of rotors. To construct a navigation system for the arbitrary 3-axis direction, the static constraint conditions are treated as dynamic equilibrium, and the analytical solution of this formulation is obtained with regard to two terms, namely attitude and height control. Moreover, the obtained analytical solution is implemented as a proportional-integral-derivative controller such that the navigation control system is fused with the attitude and height control systems optimally. To confirm the efficacy of this constructed navigation control system, navigation experiments with arbitrary azimuth direction and height are executed for a manufactured trial quadrotor system as an aerial robot and the results are estimated.

Spatial attention model based target detection for aerial robotic systems

Detecting interested targets on aerial robotic systems is a challenging task. Due to the long view distance of air-to-ground observation, the target size is small and the number is large in the scene. In addition, the target only occupies part of the image, and the complex background environment can easily cover the feature information of the target. In this paper, a novel target detection method based on spatial attention model is designed, which changes the existing methods to enhance the features of target areas by enhancing global semantic information. By learning the feature weights of different spatial locations in feature space, the method proposed can focus attention on the target regions of interest in an image, and suppress the background interference features, which enhances the feature information of the target regions, and deals with the class imbalance problem in detection. The experimental results show that the algorithm improves the detection accuracy of small air-to-ground targets and has a good detection effect for dense target areas. Compared with RefineDet, the state-of-art small target detector, our method can achieve better performance at a lower cost.

Real-Time Vibration-Based Propeller Fault Diagnosis for Multicopters

Reliable health monitoring of mechanical components in aerial robotic systems is crucial to their safe operation. The highly constrained nature of aerial systems requires that such systems operate with a minimum of sensing and computational power. This article proposes a method for the detection and diagnosis of motor/propeller degradation on a multicopter aerial robot. The proposed method works by monitoring the accelerometer output, and effectively correlates vibration power to the motor commands, allowing it to estimate the magnitude of a propeller's unbalance mass. This is done directly in the time domain with a recursive implementation. The method makes low computational and memory demands, and relies only on the accelerometer almost universally present on aerial robots, so that it may be easily implemented on existing platforms as well as new designs. Experiments show reliable detection of a faulty propeller on three distinct multicopter platforms: two quadcopters whose masses differ by more than an order of magnitude, and a hexacopter; one vehicle has brushed motors, two have brushless motors. The proposed method requires only a minimum of assumptions about the vehicle's dynamic model, and does not, e.g., require knowledge of the vehicle's center of mass or its mass moment of inertia.