Real-time Implementation and Validation of a New Hierarchical Path Planning Scheme for UAVs via Hardware-in-the-Loop Simulation

The original publication is available at www.springerlink.com.We develop a hierarchical path planning and control algorithm for a small fixed-wing UAV. Incorporating the hardware-in-the-loop (HIL) simulation environment, the hierarchical path planning and control algorithm has been validated through on-board, real-time implementation on a small autopilot. We present two distinct real-time software framework for implementation of the overall control algorithms including path planning, path smoothing, and path following. We especially emphasize the use of a real-time kernel, which shows effectiveness and robustness in accomplishing non-trivial real-time software environment. By a seamless integration of the control algorithms with a help of real-time kernel, it has been demonstrated that the UAV equipped with a small autopilot having limited computational resources manages to autonomously accomplish the mission control objective of reaching the goal while avoiding obstacles without human intervention

Adaptive and Optimal Motion Control of Multi-UAV Systems

This thesis studies trajectory tracking and coordination control problems for single and multi unmanned aerial vehicle (UAV) systems. These control problems are addressed for both quadrotor and fixed-wing UAV cases. Despite the fact that the literature has some approaches for both problems, most of the previous studies have implementation challenges on real-time systems. In this thesis, we use a hierarchical modular approach where the high-level coordination and formation control tasks are separated from low-level individual UAV motion control tasks. This separation helps efficient and systematic optimal control synthesis robust to effects of nonlinearities, uncertainties and external disturbances at both levels, independently. The modular two-level control structure is convenient in extending single-UAV motion control design to coordination control of multi-UAV systems. Therefore, we examine single quadrotor UAV trajectory tracking problems to develop advanced controllers compensating effects of nonlinearities and uncertainties, and improving robustness and optimality for tracking performance. At fi rst, a novel adaptive linear quadratic tracking (ALQT) scheme is developed for stabilization and optimal attitude control of the quadrotor UAV system. In the implementation, the proposed scheme is integrated with Kalman based reliable attitude estimators, which compensate measurement noises. Next, in order to guarantee prescribed transient and steady-state tracking performances, we have designed a novel backstepping based adaptive controller that is robust to effects of underactuated dynamics, nonlinearities and model uncertainties, e.g., inertial and rotational drag uncertainties. The tracking performance is guaranteed to utilize a prescribed performance bound (PPB) based error transformation. In the coordination control of multi-UAV systems, following the two-level control structure, at high-level, we design a distributed hierarchical (leader-follower) 3D formation control scheme. Then, the low-level control design is based on the optimal and adaptive control designs performed for each quadrotor UAV separately. As particular approaches, we design an adaptive mixing controller (AMC) to improve robustness to varying parametric uncertainties and an adaptive linear quadratic controller (ALQC). Lastly, for planar motion, especially for constant altitude flight of fixed-wing UAVs, in 2D, a distributed hierarchical (leader-follower) formation control scheme at the high-level and a linear quadratic tracking (LQT) scheme at the low-level are developed for tracking and formation control problems of the fixed-wing UAV systems to examine the non-holonomic motion case. The proposed control methods are tested via simulations and experiments on a multi-quadrotor UAV system testbed

System Architectures for Cooperative Teams of Unmanned Aerial Vehicles Interacting Physically with the Environment

Unmanned Aerial Vehicles (UAVs) have become quite a useful tool for a wide range of applications, from inspection & maintenance to search & rescue, among others. The capabilities of a single UAV can be extended or complemented by the deployment of more UAVs, so multi-UAV cooperative teams are becoming a trend. In that case, as di erent autopilots, heterogeneous platforms, and application-dependent software components have to be integrated, multi-UAV system architectures that are fexible and can adapt to the team's needs are required. In this thesis, we develop system architectures for cooperative teams of UAVs, paying special attention to applications that require physical interaction with the environment, which is typically unstructured. First, we implement some layers to abstract the high-level components from the hardware speci cs. Then we propose increasingly advanced architectures, from a single-UAV hierarchical navigation architecture to an architecture for a cooperative team of heterogeneous UAVs. All this work has been thoroughly tested in both simulation and eld experiments in di erent challenging scenarios through research projects and robotics competitions. Most of the applications required physical interaction with the environment, mainly in unstructured outdoors scenarios. All the know-how and lessons learned throughout the process are shared in this thesis, and all relevant code is publicly available.Los vehículos aéreos no tripulados (UAVs, del inglés Unmanned Aerial Vehicles) se han convertido en herramientas muy valiosas para un amplio espectro de aplicaciones, como inspección y mantenimiento, u operaciones de rescate, entre otras. Las capacidades de un único UAV pueden verse extendidas o complementadas al utilizar varios de estos vehículos simultáneamente, por lo que la tendencia actual es el uso de equipos cooperativos con múltiples UAVs. Para ello, es fundamental la integración de diferentes autopilotos, plataformas heterogéneas, y componentes software -que dependen de la aplicación-, por lo que se requieren arquitecturas multi-UAV que sean flexibles y adaptables a las necesidades del equipo. En esta tesis, se desarrollan arquitecturas para equipos cooperativos de UAVs, prestando una especial atención a aplicaciones que requieran de interacción física con el entorno, cuya naturaleza es típicamente no estructurada. Primero se proponen capas para abstraer a los componentes de alto nivel de las particularidades del hardware. Luego se desarrollan arquitecturas cada vez más avanzadas, desde una arquitectura de navegación para un único UAV, hasta una para un equipo cooperativo de UAVs heterogéneos. Todo el trabajo ha sido minuciosamente probado, tanto en simulación como en experimentos reales, en diferentes y complejos escenarios motivados por proyectos de investigación y competiciones de robótica. En la mayoría de las aplicaciones se requería de interacción física con el entorno, que es normalmente un escenario en exteriores no estructurado. A lo largo de la tesis, se comparten todo el conocimiento adquirido y las lecciones aprendidas en el proceso, y el código relevante está publicado como open-source

A flexible hardware-in-the-loop architecture for UAVs

© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.As robotic technology matures, fully autonomous robots become a realistic possibility, but demand very complex solutions to be rapidly engineered. In order to be able to quickly set up a working autonomous system, and to reduce the gap between simulated and real experiments, we propose a modular, upgradeable and flexible hardware-in-the-loop (HIL) architecture, which hybridizes the simulated and real settings. We take as use case the autonomous exploration of dense forests with UAVs, with the aim of creating useful maps for forest inspection, cataloging, or to compute other metrics such as total wood volume. As the first step in the development of the full system, in this paper we implement a fraction of this architecture, comprising assisted localization, and automatic methods for mapping, planning and motion execution. Specifically we are able to simulate the use of a 3D LIDAR endowed below an actual UAV autonomously navigating among simulated obstacles, thus the platform safety is not compromised. The full system is modular and takes profit of pieces either publicly available or easily programmed. We highlight the flexibility of the proposed HIL architecture to rapidly configure different experimental setups with a UAV in challenging terrain. Moreover, it can be extended to other robotic fields without further design. The HIL system uses the multi-platform ROS capabilities and only needs a motion capture system as external extra hardware, which is becoming standard equipment in all research labs dealing with mobile robots.Peer ReviewedPostprint (author's final draft

Multi-UAV Integrated Internet of Things System for Generating Safe Map in Post-Disaster

芝浦工業大学2019年

Integrated approaches to handle UAV actuator fault

Unmanned AerialVehicles (UAV) has historically shown to be unreliable when compared to their manned counterparts. Part of the reason is they may not be able to a ord the redundancies required to handle faults from system or cost constraints. This research explores instances when actuator fault handling may be improved with integrated approaches for small UAVs which have limited actuator redundancy. The research started with examining the possibility of handling the case where no actuator redundancy remains post fault. Two fault recovery schemes, combing control allocation and hardware means, for a Quad Rotor UAV with no redundancy upon fault event are developed to enable safe emergency landing. Inspired by the integrated approach, a proposed integrated actuator control scheme is developed, and shown to reduce the magnitude of the error dynamics when input saturation faults occur. Geometrical insights to the proposed actuator scheme are obtained. Simulations using an Aerosonde UAV model with the proposed scheme showed significant improvements to the fault tolerant stuck fault range and improved guidance tracking performance. While much research literature has previously been focused on the controller to handle actuator faults, fault tolerant guidance schemes may also be utilized to accommodate the fault. One possible advantage of using fault tolerant guidance is that it may consider the fault degradation e ects on the overall mission. A fault tolerant guidance reconfiguration method is developed for a path following mission. The method provides an additional degree of freedom in design, which allows more flexibility to the designer to meet mission requirements. This research has provided fresh insights into the handling UAV extremal actuator faults through integrated approaches. The impact of this work is to expand on the possibilities a practitioner may have for improving the fault handling capabilities of a UAV

Advanced control for miniature helicopters : modelling, design and flight test

Unmanned aerial vehicles (UAV) have been receiving unprecedented development during the past two decades. Among different types of UAVs, unmanned helicopters exhibit promising features gained from vertical-takeoff-and-landing, which make them as a versatile platform for both military and civil applications. The work reported in this thesis aims to apply advanced control techniques, in particular model predictive control (MPC), to an autonomous helicopter in order to enhance its performance and capability. First, a rapid prototyping testbed is developed to enable indoor flight testing for miniature helicopters. This testbed is able to simultaneously observe the flight state, carry out complicated algorithms and realtime control of helicopters all in a Matlab/Simulink environment, which provides a streamline process from algorithm development, simulation to flight tests. Next, the modelling and system identification for small-scale helicopters are studied. A parametric model is developed and the unknown parameters are estimated through the designed identification process. After a mathematical model of the selected helicopter is available, three MPC based control algorithms are developed focusing on different aspects in the operation of autonomous helicopters. The first algorithm is a nonlinear MPC framework. A piecewise constant scheme is used in the MPC formulation to reduce the intensive computation load. A two-level framework is suggested where the nonlinear MPC is combined with a low-level linear controller to allow its application on the systems with fast dynamics. The second algorithm solves the local path planning and the successive tracking control by using nonlinear and linear MPC, respectively. The kinematics and obstacle information are incorporated in the path planning, and the linear dynamics are used to design a flight controller. A guidance compensator dynamically links the path planner and flight controller. The third algorithm focuses on the further reduction of computational load in a MPC scheme and the trajectory tracking control in the presence of uncertainties and disturbances. An explicit nonlinear MPC is developed for helicopters to avoid online optimisation, which is then integrated with a nonlinear disturbance observer to significantly improve its robustness and disturbance attenuation. All these algorithms have been verified by flight tests for autonomous helicopters in the dedicated rapid prototyping testbed developed in this thesis.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Planejamento para missões autônomas persistentes cooperativas de longo prazo

Orientador: Andre Ricardo FioravantiDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia MecânicaResumo: Uma metodologia para abordar missões autônomas persistentes a longo prazo é apresentada juntamente com uma formalização geral do problema em hipóteses simples. É derivada uma realização dessa metodologia que reduz o problema geral para subproblemas de construção de caminho e de otimização combinatória, que são tratados com heurísticas para a computação de solução viável. Quatro estudos de caso são propostos e resolvidos com esta metodologia, mostrando que é possível obter caminhos contínuos ótimos ou subótimos aceitáveis a partir de ma representação discreta e elucidando algumas propriedades de solução nesses diferentes cenários, construindo bases para futuras escolhas educadas entre o uso de métodos exatos ou heurísticosAbstract: A Methodology for tackling Persistent Long Term Autonomous Missions is presented along with a general formalization of the problem upon simple assumptions. A realization of this methodology is derived which reduces the overall problem to a path construction and a combinatorial optimization subproblems, which are treated themselves with heuristics for feasible solution computation. Four case studies are proposed and solved with this methodology, showing that it is possible to obtain optimal or acceptable suboptimal continuous paths from a discrete representation, and elucidating some solution properties in these different scenarios, building bases for future educated choices between use of exact methods over heuristicsMestradoMecanica dos Sólidos e Projeto MecanicoMestre em Engenharia Mecânica1687532CAPE

Feature Papers of Drones - Volume I

[EN] The present book is divided into two volumes (Volume I: articles 1–23, and Volume II: articles 24–54) which compile the articles and communications submitted to the Topical Collection ”Feature Papers of Drones” during the years 2020 to 2022 describing novel or new cutting-edge designs, developments, and/or applications of unmanned vehicles (drones). Articles 1–8 are devoted to the developments of drone design, where new concepts and modeling strategies as well as effective designs that improve drone stability and autonomy are introduced. Articles 9–16 focus on the communication aspects of drones as effective strategies for smooth deployment and efficient functioning are required. Therefore, several developments that aim to optimize performance and security are presented. In this regard, one of the most directly related topics is drone swarms, not only in terms of communication but also human-swarm interaction and their applications for science missions, surveillance, and disaster rescue operations. To conclude with the volume I related to drone improvements, articles 17–23 discusses the advancements associated with autonomous navigation, obstacle avoidance, and enhanced flight plannin

Cooperative Systems

Master'sMASTER OF ENGINEERIN