UAV Optimal Cooperative Obstacle Avoidance and Target Tracking in Dynamic Stochastic Environments

Cette thèse propose une stratégie de contrôle avancée pour guider une flotte d'aéronefs sans pilote (UAV) dans un environnement à la fois stochastique et dynamique. Pour ce faire, un simulateur de vol 3D a été développé avec MATLAB® pour tester les algorithmes de la stratégie de guidage en fonctions de différents scénarios. L'objectif des missions simulées est de s'assurer que chaque UAV intercepte une cible ellipsoïdale mobile tout en évitant une panoplie d'obstacles ellipsoïdaux mobiles détectés en route. Les UAVs situés à l'intérieur des limites de communication peuvent coopérer afin d'améliorer leurs performances au cours de la mission. Le simulateur a été conçu de façon à ce que les UAV soient dotés de capteurs et d'appareils de communication de portée limitée. De plus, chaque UAV possède un pilote automatique qui stabilise l'aéronef en vol et un planificateur de trajectoires qui génère les commandes à envoyer au pilote automatique. Au coeur du planificateur de trajectoires se trouve un contrôleur prédictif à horizon fuyant qui détermine les commandes à envoyer à l'UAV. Ces commandes optimisent un critère de performance assujetti à des contraintes. Le critère de performance est conçu de sorte que les UAV atteignent les objectifs de la mission, alors que les contraintes assurent que les commandes générées adhèrent aux limites de manoeuvrabilité de l'aéronef. La planification de trajectoires pour UAV opérant dans un environnement dynamique et stochastique dépend fortement des déplacements anticipés des objets (obstacle, cible). Un filtre de Kalman étendu est donc utilisé pour prédire les trajectoires les plus probables des objets à partir de leurs états estimés. Des stratégies de poursuite et d'évitement ont aussi été développées en fonction des trajectoires prédites des objets détectés. Pour des raisons de sécurité, la conception de stratégies d'évitement de collision à la fois efficaces et robustes est primordiale au guidage d'UAV. Une nouvelle stratégie d'évitement d'obstacles par approche probabiliste a donc été développée. La méthode cherche à minimiser la probabilité de collision entre l'UAV et tous ses obstacles détectés sur l'horizon de prédiction, tout en s'assurant que, à chaque pas de prédiction, la probabilité de collision entre l'UAV et chacun de ses obstacles détectés ne surpasse pas un seuil prescrit. Des simulations sont présentées au cours de cette thèse pour démontrer l'efficacité des algorithmes proposés

Fixed-wing UAV tracking of evasive targets in 3-dimensional space

In this thesis, we explore the development of autonomous tracking and interception strategies for single and multiple fixed-wing Unmanned Aerial Vehicles (UAVs) pursuing single or multiple evasive targets in 3-dimensional (3D) space. We considered a scenario where we intend to protect high-value facilities from adversarial groups employing ground-based vehicles and quadrotor swarms and focused on solving the target tracking problem. Accordingly, we refined a min-max optimal control algorithm for fixed-wing UAVs tracking ground-based targets, by introducing constraints on bank angles and turn rates to enhance actuator reliability when pursuing agile and evasive targets. An intelligent and persistent evasive control strategy for the target was also devised to ensure robust performance testing and optimisation. These strategies were extended to 3D space, incorporating three altitude control algorithms to facilitate flexible UAV altitude control, leveraging various parameters such as desired UAV altitude and image size on the tracking camera lens. A novel evasive quadrotor algorithm was introduced, systematically testing UAV tracking efficacy against various evasive scenarios while implementing anti-collision measures to ensure UAV safety and adaptive optimisation improve the achieved performance. Using decentralised control strategies, cooperative tracking by multiple UAVs of single evasive quadrotor-type and dynamic target clusters was developed along with a new altitude control strategy and task assignment logic for efficient target interception. Lastly, a countermeasure strategy for tracking and neutralising non-cooperative adversarial targets within restricted airspace was implemented, using both Nonlinear Model Predictive Control (NMPC) and optimal controllers. The major contributions of this thesis include optimal control strategies, evasive target control, 3D target tracking, altitude control, cooperative multi-UAV tracking, adaptive optimisation, high-precision projectile algorithms, and countermeasures. We envision practical applications of the findings from this research in surveillance, security, search and rescue, agriculture, environmental monitoring, drone defence, and autonomous delivery systems. Future efforts to extend this research could explore adaptive evasion, enhanced collaborative UAV swarms, machine learning integration, sensor technologies, and real-world testing

Military Aviation Principles

Military all over the world uses military aircraft in both offensive and defensive purposes. In offensive role, these aircraft are used in destroying enemy’s vital installations, air strips, ordnance depots and supplies. In defensive role, it provides close air support to land-based army and also deters the threats of enemy air strike. In naval warfare, military aircraft plays a significant role to detect and neutralize submarines and warships to keep the seacoast free from enemy attack. Military aircraft also provides logistic supply to forward bases, conducting airlift (cargo and troops), and participates in rescue operations during national disaster. Military aviation includes both transport and warcraft and consisting of fixed wing aircraft, rotary-wing aircraft (RWA) and unmanned aerial vehicle (UAV). From the early days of world war, it has been realized that air power supremacy is vital for winning a war as well as maintaining the sovereignty of any country. This chapter discusses basic flight mechanics, types and roles of aircraft, safety considerations and design and certification procedures

Intelligent Autonomous Decision-Making and Cooperative Control Technology of High-Speed Vehicle Swarms

This book is a reprint of the Special Issue “Intelligent Autonomous Decision-Making and Cooperative Control Technology of High-Speed Vehicle Swarms”,which was published in Applied Sciences

Autonomous aerial robot for high-speed search and intercept applications

In recent years, high-speed navigation and environment interaction in the context of aerial robotics has become a field of interest for several academic and industrial research studies. In particular, Search and Intercept (SaI) applications for aerial robots pose a compelling research area due to their potential usability in several environments. Nevertheless, SaI tasks involve a challenging development regarding sensory weight, onboard computation resources, actuation design, and algorithms for perception and control, among others. In this work, a fully autonomous aerial robot for high-speed object grasping has been proposed. As an additional subtask, our system is able to autonomously pierce balloons located in poles close to the surface. Our first contribution is the design of the aerial robot at an actuation and sensory level consisting of a novel gripper design with additional sensors enabling the robot to grasp objects at high speeds. The second contribution is a complete software framework consisting of perception, state estimation, motion planning, motion control, and mission control in order to rapidly and robustly perform the autonomous grasping mission. Our approach has been validated in a challenging international competition and has shown outstanding results, being able to autonomously search, follow, and grasp a moving object at 6 m/s in an outdoor environment.Agencia Estatal de InvestigaciónKhalifa Universit

Bespilotne letjelice: novo doba u zrakoplovstvu

The phenomenon of unmanned and remotely controlled (wireless) devices and craft has been present for some time already in all modes of transport: air, land, space, underwater. An important distinctive feature of aircraft as opposed to land vehicles lies however in the third dimension of their evolution, which complicates the pertinent regulatory framework. In the present regime a drone falls within the definition of a power-driven aircraft (Annex 7 to the Chicago Convention), whether it is an aeroplane (fixed wing), an airship (lighter than air) or a helicopter (rotary wing). Annex 2 to the Chicago Convention recognizes the category of remotely piloted aircraft, but Art 8 of the Chicago Convention subjects the operation of such devices to national authorization. The consequence at present is a regulatory environment that differs between the respective countries: from permissive (regulatory vacuum) to restrictive (total ban). Legislators/regulators are hard at work developing new rules to make up a legal framework that will accommodate this new economic activity and integrate it into the existing aviation regime (USA, Italy, etc.). Given the international nature of aviation and in order to accommodate the international use of drones, an internationally coordinated approach is required to develop a harmonized regime. ICAO has already published a Manual on Remotely Piloted Aircraft Systems (RPAS) to provide guidance on drone matters in the legislative/regulatory process. ICAO and the EU have started to develop regulations. There seems to be a general consensus that unmanned aircraft must be allowed to operate without segregation from other air space users. The commercial use of drones has an impact on safety that must be solved. The security risk is to be mitigated. The potential invasion of privacy is a serious concern, as well as the tort of trespassing in case of non-authorised low level over-flight of private property. The awareness of the regulatory and operational restrictions amongst users will require the organisation of a public information campaign.Fenomen bespilotnih uređaja i vozila na daljinsko (bežično) upravljanje prisutan je već neko vrijeme, i to u raznim oblicima prijevoza: zemaljskom, zračnom, svemirskom i podvodnom. No, važno razlikovno obilježje letjelica u odnosu na zemaljska vozila nalazi se u trećoj dimenziji njihove evolucije, što komplicira izradu regulacijskog okvira. Prema trenutačnom uređenju bespilotna letjelica ulazi u definiciju letjelice na motorni pogon (prilog 7. Čikaške konvencije) bez obzira na to je li riječ o zrakoplovu s nepokretnim ili pokretnim krilom, ili zrakoplovu lakšem od zraka. Prilog 2. Čikaške konvencije prepoznaje kategoriju letjelice na daljinsko upravljanje, ali prema članku 8. Konvencije ona podliježe nacionalnom uređenju. Stoga se regulacijski okvir trenutačno veoma razlikuje od države do države: od liberalnog (regulatorni vakuum) do restriktivnog (potpuna zabrana). Zakonodavci/regulatori ubrzano rade na razvoju novih pravila kako bi stvorili pravni okvir koji će podržati tu novu gospodarsku djelatnost i integrirati je u postojeći zrakoplovni sustav (SAD, Italija itd.). S obzirom na međunarodnu prirodu zrakoplovstva i međunarodnu upotrebu bespilotnih letjelica potreban je međunarodno koordinirani pristup u razvoju jednog usklađenog sustava. Međunarodna organizacija civilnog zrakoplovstva (ICAO) već je izdala Priručnik za sustave letjelica na daljinsko upravljanje (Remotely Piloted Aircraft Systems), koji sadržava smjernice za izradu relevantnog zakonodavstva/regulative. ICAO i EU rade na razvoju pravnog okvira. Čini se da postoji opći konsenzus da bespilotnim letjelicama mora biti dopušten promet bez odvajanja od ostalih korisnika zračnog prostora. Komercijalna upotreba takvih letjelica ima učinak na sigurnost koji svakako treba riješiti. Sigurnosne je rizike potrebno svesti na najmanju mogući mjeru. Moguće ugrožavanje privatnosti ozbiljan je problem, jednako kao i prijestup smetanja posjeda u slučaju nedopuštenog niskog prelijetanja zemlje u privatnom vlasništvu. Bit će potrebno organizirati informativne kampanje kako bi se među korisnicima podigla svijest o regulatornim i operativnim ograničenjima

Autonomous Visual Servo Robotic Capture of Non-cooperative Target

This doctoral research develops and validates experimentally a vision-based control scheme for the autonomous capture of a non-cooperative target by robotic manipulators for active space debris removal and on-orbit servicing. It is focused on the final capture stage by robotic manipulators after the orbital rendezvous and proximity maneuver being completed. Two challenges have been identified and investigated in this stage: the dynamic estimation of the non-cooperative target and the autonomous visual servo robotic control. First, an integrated algorithm of photogrammetry and extended Kalman filter is proposed for the dynamic estimation of the non-cooperative target because it is unknown in advance. To improve the stability and precision of the algorithm, the extended Kalman filter is enhanced by dynamically correcting the distribution of the process noise of the filter. Second, the concept of incremental kinematic control is proposed to avoid the multiple solutions in solving the inverse kinematics of robotic manipulators. The proposed target motion estimation and visual servo control algorithms are validated experimentally by a custom built visual servo manipulator-target system. Electronic hardware for the robotic manipulator and computer software for the visual servo are custom designed and developed. The experimental results demonstrate the effectiveness and advantages of the proposed vision-based robotic control for the autonomous capture of a non-cooperative target. Furthermore, a preliminary study is conducted for future extension of the robotic control with consideration of flexible joints

Wide-Area Surveillance System using a UAV Helicopter Interceptor and Sensor Placement Planning Techniques

This project proposes and describes the implementation of a wide-area surveillance system comprised of a sensor/interceptor placement planning and an interceptor unmanned aerial vehicle (UAV) helicopter. Given the 2-D layout of an area, the planning system optimally places perimeter cameras based on maximum coverage and minimal cost. Part of this planning system includes the MATLAB implementation of Erdem and Sclaroff’s Radial Sweep algorithm for visibility polygon generation. Additionally, 2-D camera modeling is proposed for both fixed and PTZ cases. Finally, the interceptor is also placed to minimize shortest-path flight time to any point on the perimeter during a detection event. Secondly, a basic flight control system for the UAV helicopter is designed and implemented. The flight control system’s primary goal is to hover the helicopter in place when a human operator holds an automatic-flight switch. This system represents the first step in a complete waypoint-navigation flight control system. The flight control system is based on an inertial measurement unit (IMU) and a proportional-integral-derivative (PID) controller. This system is implemented using a general-purpose personal computer (GPPC) running Windows XP and other commercial off-the-shelf (COTS) hardware. This setup differs from other helicopter control systems which typically use custom embedded solutions or micro-controllers. Experiments demonstrate the sensor placement planning achieving \u3e90% coverage at optimized-cost for several typical areas given multiple camera types and parameters. Furthermore, the helicopter flight control system experiments achieve hovering success over short flight periods. However, the final conclusion is that the COTS IMU is insufficient for high-speed, high-frequency applications such as a helicopter control system

Deployment and navigation of aerial drones for sensing and interacting applications

Existing research recognises the critical role played by Unmanned Aerial Vehicles (UAVs) (also referred to as drones) to numerous civilian applications. Typical drone applications include surveillance, wireless communication, agriculture, among many others. One of the biggest challenges is to determine the deployment and navigation of the drones to benefit the most for different applications. Many research questions have been raised about this topic. For example, drone-enabled wildlife monitoring has received much attention in recent years. Unfortunately, this approach results in significant disturbance to different species of wild animals. Moreover, with the capability of rapidly moving communication supply towards demand when required, the drone equipped with a base station, i.e., drone-cell, is becoming a promising solution for providing cellular networks to victims and rescue teams in disaster-affected areas. However, few studies have investigated the optimal deployments of multiple drone-cells with limited backhaul communication distances. In addition, the use of autonomous drones as flying interactors for many real-life applications has not been sufficiently discussed. With superior maneuverability, drone-enabled autonomous aerial interacting can potentially be used on shark attack prevention and animal herding. Nevertheless, previous studies of autonomous drones have not dealt with such applications in much detail. This thesis explores the solutions to all the mentioned research questions, with a particular focus on the deployment and navigation of the drones. First, we provide one of the first investigations into reducing the negative impacts of wildlife monitoring drones by navigation control. Second, we study the optimal placement of a group of drone-cells with limited backhaul communication ranges, aims to maximise the number of served users. Third, we propose a novel method named ‘drone shark shield’, which uses communicating autonomous drones to intervene and prevent shark attacks for protecting swimmers and surfers. Lastly, we introduce one of the first autonomous drone herding systems for mustering a large number of farm animals efficiently. Simulations have been conducted to verify the effectiveness of the proposed approaches. We believe that our findings in this thesis shed new light on the fundamental benefits of autonomous civilian drones