72 research outputs found
Autonomous Obstacle Collision Avoidance System for UAVs in rescue operations
The Unmanned Aerial Vehicles (UAV) and its applications are growing for both civilian and
military purposes. The operability of an UAV proved that some tasks and operations can be
done easily and at a good cost-efficiency ratio.
Nowadays, an UAV can perform autonomous tasks, by using waypoint mission navigation
using a GPS sensor. These autonomous tasks are also called missions. It is very useful to certain
UAV applications, such as meteorology, vigilance systems, agriculture, environment mapping
and search and rescue operations.
One of the biggest problems that an UAV faces is the possibility of collision with other objects
in the flight area. This can cause damage to surrounding area structures, humans or the UAV
itself. To avoid this, an algorithm was developed and implemented in order to prevent UAV
collision with other objects.
“Sense and Avoid” algorithm was developed as a system for UAVs to avoid objects in collision
course. This algorithm uses a laser distance sensor called LiDAR (Light Detection and
Ranging), to detect objects facing the UAV in mid-flights. This light sensor is connected to an
on-board hardware, Pixhawk’s flight controller, which interfaces its communications with
another hardware: Raspberry Pi. Communications between Ground Control Station or RC
controller are made via Wi-Fi telemetry or Radio telemetry.
“Sense and Avoid” algorithm has two different modes: “Brake” and “Avoid and Continue”.
These modes operate in different controlling methods. “Brake” mode is used to prevent UAV
collisions with objects when controlled by a human operator that is using a RC controller.
“Avoid and Continue” mode works on UAV’s autonomous modes, avoiding collision with
objects in sight and proceeding with the ongoing mission.
In this dissertation, some tests were made in order to evaluate the “Sense and Avoid”
algorithm’s overall performance. These tests were done in two different environments: A 3D
simulated environment and a real outdoor environment. Both modes worked successfully on a
simulated 3D environment, and “Brake” mode on a real outdoor, proving its concepts.Os veículos aéreos não tripulados (UAV) e as suas aplicações estão cada vez mais a ser
utilizadas para fins civis e militares. A operacionalidade de um UAV provou que algumas
tarefas e operações podem ser feitas facilmente e com uma boa relação de custo-benefício. Hoje
em dia, um UAV pode executar tarefas autonomamente, usando navegação por waypoints e um
sensor de GPS. Essas tarefas autónomas também são designadas de missões. As missões
autónomas poderão ser usadas para diversos propósitos, tais como na meteorologia, sistemas
de vigilância, agricultura, mapeamento de áreas e operações de busca e salvamento. Um dos
maiores problemas que um UAV enfrenta é a possibilidade de colisão com outros objetos na
área, podendo causar danos às estruturas envolventes, aos seres humanos ou ao próprio UAV.
Para evitar tais ocorrências, foi desenvolvido e implementado um algoritmo para evitar a colisão
de um UAV com outros objetos.
O algoritmo "Sense and Avoid" foi desenvolvido como um sistema para UAVs de modo a evitar
objetos em rota de colisão. Este algoritmo utiliza um sensor de distância a laser chamado
LiDAR (Light Detection and Ranging), para detetar objetos que estão em frente do UAV. Este
sensor é ligado a um hardware de bordo, a controladora de voo Pixhawk, que realiza as suas
comunicações com outro hardware complementar: o Raspberry Pi. As comunicações entre a
estação de controlo ou o operador de comando RC são feitas via telemetria Wi-Fi ou telemetria
por rádio. O algoritmo "Sense and Avoid" tem dois modos diferentes: o modo "Brake" e modo
"Avoid and Continue". Estes modos operam em diferentes métodos de controlo do UAV. O
modo "Brake" é usado para evitar colisões com objetos quando controlado via controlador RC
por um operador humano. O modo "Avoid and Continue" funciona nos modos de voo
autónomos do UAV, evitando colisões com objetos à vista e prosseguindo com a missão em
curso. Nesta dissertação, alguns testes foram realizados para avaliar o desempenho geral do
algoritmo "Sense and Avoid". Estes testes foram realizados em dois ambientes diferentes: um
ambiente de simulação em 3D e um ambiente ao ar livre. Ambos os modos obtiveram
funcionaram com sucesso no ambiente de simulação 3D e o mode “Brake” no ambiente real,
provando os seus conceitos
Safety mechanisms for the reliable operation of 3D vehicles
The safety and reliability of unmanned vehicles is a growing concern in our modern society. This work proposes and implements mechanisms to minimize risks in the operation of 3D vehicles. A brief analysis is performed to identify high priority risks and low complexity solutions are proposed in order to avoid or minimize their impact. To cope with critical power failures, an autonomous current monitoring system was studied and implemented after analyzing two different techniques: resistive and magnetic current sensing. Furthermore, a fall detection system capable of detecting rotational and free falls was developed and evaluated. Lastly, an obstacle detection and avoidance system relying on multiple smart sensors was proposed. Several simulation tests were performed for different velocities to obtain processing delays and stopping times and thus, the minimal safe flying distance for the avoidance of obstacles.A segurança na operação fiável de veículos não tripulados é uma preocupação crescente na nossa sociedade moderna. Este trabalho propõe e implementa mecanismos para minimizar os riscos no manuseamento destes veículos. Uma breve análise é realizada para identificar os componentes com maior risco de ocorrerem problemas e soluções de baixa complexidade são propostas a fim de evitar ou minimizar o seu impacto. Para lidar com falhas de energia críticas, um sistema de monitorização de corrente foi estudado e implementado após analisar duas técnicas diferentes: detecção de corrente resistiva e magnética. Além disso, foi desenvolvido e avaliado um sistema de detecção de quedas rotacionais e livres. Por último, foi proposto um sistema de detecção e anti-colisão de obstáculos baseado em múltiplos sensores inteligentes. Diversos testes de simulação foram realizados para obter atrasos de processamento e tempos de travagem. Deste modo foi possível calcular a distância de segurança mínima de travagem face à detecção de um obstáculo
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
MRS Drone: A Modular Platform for Real-World Deployment of Aerial Multi-Robot Systems
This paper presents a modular autonomous Unmanned Aerial Vehicle (UAV)
platform called the Multi-robot Systems (MRS) Drone that can be used in a large
range of indoor and outdoor applications. The MRS Drone features unique
modularity with respect to changes in actuators, frames, and sensory
configuration. As the name suggests, the platform is specially tailored for
deployment within a MRS group. The MRS Drone contributes to the
state-of-the-art of UAV platforms by allowing smooth real-world deployment of
multiple aerial robots, as well as by outperforming other platforms with its
modularity. For real-world multi-robot deployment in various applications, the
platform is easy to both assemble and modify. Moreover, it is accompanied by a
realistic simulator to enable safe pre-flight testing and a smooth transition
to complex real-world experiments. In this manuscript, we present mechanical
and electrical designs, software architecture, and technical specifications to
build a fully autonomous multi UAV system. Finally, we demonstrate the full
capabilities and the unique modularity of the MRS Drone in various real-world
applications that required a diverse range of platform configurations.Comment: 49 pages, 39 figures, accepted for publication to the Journal of
Intelligent & Robotic System
Design and implementation of UAV performance validation system
Abstract. This thesis aims for design and implementation of a system for drone performance measurements, which can be used for validation of different drones for research projects accordingly. Additionally, the device should be able to be used as a part of a hardware-in-loop -system with simulators in drone research. The primary goal for this thesis is to build a system which helps to document different drone properties efficiently and safely. This is done with a system that consists of a robust frame, a force and torque measuring transducer, a drone stabilizing unit, a data logging system, and a remote-control power supply. For controlling the system, user interface was created to control the data stream, the drone stabilizing unit, and the power supply.
This thesis includes a literature review of drone general classification properties and legal regulations. Short review of drone usage and selection criteria in industry and research is conducted, as well as in-depth review of the drone components and their relation to overall performance of the drone. The thesis also contains literature review of force and torque measuring theory, and other drone performance measuring units. The functionality of the designed unit is tested by building a drone from spare components, and valuating its performance based on e.g., lift generation, power consumption and visual behavior of the drone. Measured data is documented, and with the documents, drone’s suitability for future research projects can be assessed. According to the results, the unit can be used to evaluate drone’s performance, and groundwork for Hardware-in-loop simulator connection for drone research. The testing unit and the data recordings as well as the built testing drone stays within the research facility for further development.UAV testausjärjestelmän suunnittelu ja toteutus. Tiivistelmä. Tässä diplomityössä suunnitellaan ja valmistetaan droonien suorituskykyä mittaava tutkimuslaitteisto, jonka avulla voidaan arvioida erilaisten droonien soveltuvuutta tutkimusprojekteihin tapauskohtaisesti. Työssä tavoitellaan helppokäyttöistä järjestelmää, jonka avulla itse tehtyjen droonien ominaisuuksia voidaan dokumentoida turvallisesti ja tehokkaasti. Työssä perehdytään droonien luokitteluun tutustumalla voimassa oleviin säädöksiin, sekä droonin suorituskykyä kuvaaviin ominaisuuksiin. Työssä tarkastellaan droonien käyttöä eri aloilla arvioiden esiin nousseita droonin valintaperusteita ja ominaisuuksia. Tämän jälkeen tutustutaan droonien rakenteeseen ja ominaisuuksiin. Voiman mittauksen teoriaan sekä kehitettyihin mittausmenetelmiin tutustutaan tukemaan anturivalintaa. Suunniteltu järjestelmä koostuu tukevasta rungosta, voiman mittaukseen soveltuvasta anturista, droonin vakauttamisen kokonaisuudesta, datan keräysjärjestelmästä sekä etäohjattavasta virtalähteestä. Laitteiston ohjaukseen luotiin rajapinta, jonka kautta järjestelmää voidaan hallita. Järjestelmän toimivuus todettiin kahdella mittauskäyttöön soveltuvalla droonilla, joiden suorituskykyä arvioitiin droonien ominaisuuksien, sekä visuaalisen käyttäytymisen avulla. Mittauksien tulokset dokumentoitiin, ja dokumentaation perusteella voidaan arvioida sekä tutkimuslaitteiston toimivuutta, että mitattujen droonien soveltuvuutta tulevissa tutkimusprojekteissa. Mittausten perusteella voidaan todeta laitteen soveltuvan droonien suorituskyvyn mittaamiseen, sekä pohjatyöksi simulaattorikytkentään. Mittalaitteisto sekä mittaustulokset jäävät Biomimetiikka ja älykkäät järjestelmät -tutkimusyksikön käyttöön droonitutkimuksen tueksi
Vertical Take-off and Landing Autonomous Aircraft Design
This project addresses the design, analysis, and and construction of an autonomous fixed-wing/rotorcraft hybrid aircraft capable of vertical take-off and landing. Autonomy is addressed to enable obstacle avoidance, visual detection of a landing target area, and accurate landing. The designed aircraft consists of a ducted main rotor and two smaller tilt-rotors, and is based on a similar design from the literature. This report provides detailed analyses of the aircraft\u27s aerodynamic and structural properties, dynamics and stability, propulsion, and power. The development of onboard autonomy using a 3D depth sensor is presented. Simulations of stabilizing controllers are presented. The construction of a prototype aircraft and its preliminary flight test results are reported
A Review on IoT Deep Learning UAV Systems for Autonomous Obstacle Detection and Collision Avoidance
[Abstract] Advances in Unmanned Aerial Vehicles (UAVs), also known as drones, offer unprecedented opportunities to boost a wide array of large-scale Internet of Things (IoT) applications. Nevertheless, UAV platforms still face important limitations mainly related to autonomy and weight that impact their remote sensing capabilities when capturing and processing the data required for developing autonomous and robust real-time obstacle detection and avoidance systems. In this regard, Deep Learning (DL) techniques have arisen as a promising alternative for improving real-time obstacle detection and collision avoidance for highly autonomous UAVs. This article reviews the most recent developments on DL Unmanned Aerial Systems (UASs) and provides a detailed explanation on the main DL techniques. Moreover, the latest DL-UAV communication architectures are studied and their most common hardware is analyzed. Furthermore, this article enumerates the most relevant open challenges for current DL-UAV solutions, thus allowing future researchers to define a roadmap for devising the new generation affordable autonomous DL-UAV IoT solutions.Xunta de Galicia; ED431C 2016-045Xunta de Galicia; ED431C 2016-047Xunta de Galicia; , ED431G/01Centro Singular de Investigación de Galicia; PC18/01Agencia Estatal de Investigación de España; TEC2016-75067-C4-1-
Optimal Multi-UAV Trajectory Planning for Filming Applications
Teams of multiple Unmanned Aerial Vehicles (UAVs) can be used to record large-scale
outdoor scenarios and complementary views of several action points as a promising
system for cinematic video recording. Generating the trajectories of the UAVs plays
a key role, as it should be ensured that they comply with requirements for system
dynamics, smoothness, and safety. The rise of numerical methods for nonlinear
optimization is finding a
ourishing field in optimization-based approaches to multi-
UAV trajectory planning. In particular, these methods are rather promising for
video recording applications, as they enable multiple constraints and objectives to
be formulated, such as trajectory smoothness, compliance with UAV and camera
dynamics, avoidance of obstacles and inter-UAV con
icts, and mutual UAV visibility.
The main objective of this thesis is to plan online trajectories for multi-UAV teams in
video applications, formulating novel optimization problems and solving them in real
time.
The thesis begins by presenting a framework for carrying out autonomous cinematography
missions with a team of UAVs. This framework enables media directors
to design missions involving different types of shots with one or multiple cameras,
running sequentially or concurrently. Second, the thesis proposes a novel non-linear
formulation for the challenging problem of computing optimal multi-UAV trajectories
for cinematography, integrating UAV dynamics and collision avoidance constraints,
together with cinematographic aspects such as smoothness, gimbal mechanical limits,
and mutual camera visibility. Lastly, the thesis describes a method for autonomous
aerial recording with distributed lighting by a team of UAVs. The multi-UAV trajectory
optimization problem is decoupled into two steps in order to tackle non-linear cinematographic aspects and obstacle avoidance at separate stages. This allows the
trajectory planner to perform in real time and to react online to changes in dynamic
environments.
It is important to note that all the methods in the thesis have been validated
by means of extensive simulations and field experiments. Moreover, all the software
components have been developed as open source.Los equipos de vehículos aéreos no tripulados (UAV) son sistemas prometedores para grabar
eventos cinematográficos, en escenarios exteriores de grandes dimensiones difíciles de cubrir
o para tomar vistas complementarias de diferentes puntos de acción. La generación de
trayectorias para este tipo de vehículos desempeña un papel fundamental, ya que debe
garantizarse que se cumplan requisitos dinámicos, de suavidad y de seguridad.
Los enfoques basados en la optimización para la planificación de trayectorias de múltiples
UAVs se pueden ver beneficiados por el auge de los métodos numéricos para la resolución de
problemas de optimización no lineales. En particular, estos métodos son bastante
prometedores para las aplicaciones de grabación de vídeo, ya que permiten formular múltiples
restricciones y objetivos, como la suavidad de la trayectoria, el cumplimiento de la dinámica
del UAV y de la cámara, la evitación de obstáculos y de conflictos entre UAVs, y la visibilidad
mutua.
El objetivo principal de esta tesis es planificar trayectorias para equipos multi-UAV en
aplicaciones de vídeo, formulando novedosos problemas de optimización y resolviéndolos en
tiempo real.
La tesis comienza presentando un marco de trabajo para la realización de misiones
cinematográficas autónomas con un equipo de UAVs. Este marco permite a los directores de
medios de comunicación diseñar misiones que incluyan diferentes tipos de tomas con una o
varias cámaras, ejecutadas de forma secuencial o concurrente. En segundo lugar, la tesis
propone una novedosa formulación no lineal para el difícil problema de calcular las
trayectorias óptimas de los vehículos aéreos no tripulados en cinematografía, integrando en el
problema la dinámica de los UAVs y las restricciones para evitar colisiones, junto con aspectos
cinematográficos como la suavidad, los límites mecánicos del cardán y la visibilidad mutua de
las cámaras. Por último, la tesis describe un método de grabación aérea autónoma con
iluminación distribuida por un equipo de UAVs. El problema de optimización de trayectorias se
desacopla en dos pasos para abordar los aspectos cinematográficos no lineales y la evitación
de obstáculos en etapas separadas. Esto permite al planificador de trayectorias actuar en
tiempo real y reaccionar en línea a los cambios en los entornos dinámicos.
Es importante señalar que todos los métodos de la tesis han sido validados mediante extensas
simulaciones y experimentos de campo. Además, todos los componentes del software se han
desarrollado como código abierto
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