672 research outputs found
Optimal Trajectory Planning for Cinematography with Multiple Unmanned Aerial Vehicles
This paper presents a method for planning optimal trajectories with a team of
Unmanned Aerial Vehicles (UAVs) performing autonomous cinematography. The
method is able to plan trajectories online and in a distributed manner,
providing coordination between the UAVs. We propose a novel non-linear
formulation for this challenging problem of computing multi-UAV optimal
trajectories for cinematography; integrating UAVs dynamics and collision
avoidance constraints, together with cinematographic aspects like smoothness,
gimbal mechanical limits and mutual camera visibility. We integrate our method
within a hardware and software architecture for UAV cinematography that was
previously developed within the framework of the MultiDrone project; and
demonstrate its use with different types of shots filming a moving target
outdoors. We provide extensive experimental results both in simulation and
field experiments. We analyze the performance of the method and prove that it
is able to compute online smooth trajectories, reducing jerky movements and
complying with cinematography constraints.Comment: This paper has been published as: Optimal trajectory planning for
cinematography with multiple Unmanned Aerial Vehicles. Alfonso Alcantara and
Jesus Capitan and Rita Cunha and Anibal Ollero. Robotics and Autonomous
Systems. 103778 (2021) 10.1016/j.robot.2021.10377
Aerial Field Robotics
Aerial field robotics research represents the domain of study that aims to
equip unmanned aerial vehicles - and as it pertains to this chapter,
specifically Micro Aerial Vehicles (MAVs)- with the ability to operate in
real-life environments that present challenges to safe navigation. We present
the key elements of autonomy for MAVs that are resilient to collisions and
sensing degradation, while operating under constrained computational resources.
We overview aspects of the state of the art, outline bottlenecks to resilient
navigation autonomy, and overview the field-readiness of MAVs. We conclude with
notable contributions and discuss considerations for future research that are
essential for resilience in aerial robotics.Comment: Accepted in the Encyclopedia of Robotics, Springe
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
The MRS UAV System: Pushing the Frontiers of Reproducible Research, Real-world Deployment, and Education with Autonomous Unmanned Aerial Vehicles
We present a multirotor Unmanned Aerial Vehicle control (UAV) and estimation
system for supporting replicable research through realistic simulations and
real-world experiments. We propose a unique multi-frame localization paradigm
for estimating the states of a UAV in various frames of reference using
multiple sensors simultaneously. The system enables complex missions in GNSS
and GNSS-denied environments, including outdoor-indoor transitions and the
execution of redundant estimators for backing up unreliable localization
sources. Two feedback control designs are presented: one for precise and
aggressive maneuvers, and the other for stable and smooth flight with a noisy
state estimate. The proposed control and estimation pipeline are constructed
without using the Euler/Tait-Bryan angle representation of orientation in 3D.
Instead, we rely on rotation matrices and a novel heading-based convention to
represent the one free rotational degree-of-freedom in 3D of a standard
multirotor helicopter. We provide an actively maintained and well-documented
open-source implementation, including realistic simulation of UAV, sensors, and
localization systems. The proposed system is the product of years of applied
research on multi-robot systems, aerial swarms, aerial manipulation, motion
planning, and remote sensing. All our results have been supported by real-world
system deployment that shaped the system into the form presented here. In
addition, the system was utilized during the participation of our team from the
CTU in Prague in the prestigious MBZIRC 2017 and 2020 robotics competitions,
and also in the DARPA SubT challenge. Each time, our team was able to secure
top places among the best competitors from all over the world. On each
occasion, the challenges has motivated the team to improve the system and to
gain a great amount of high-quality experience within tight deadlines.Comment: 28 pages, 20 figures, submitted to Journal of Intelligent & Robotic
Systems (JINT), for the provided open-source software see
http://github.com/ctu-mr
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
Safe Autonomous Aerial Surveys of Historical Building Interiors
Cílem této práce je vývoj systému pro bezpečný autonomní průzkum interiérů historických budov za pomocí vícerotorových autonomních bezpilotních helikoptér. Navržené řešení zahrnuje metodu pro sledování požadované trajektorie založené na přístupu lídr-následovník a prediktivním řízení, detekci potenciálních chyb a systému pro řízení mise, který zprostředkovává spolupráci mezi jednotlivými členy formace a korektní reakci na nastalé chyby jednotlivých podsystémů. Návrh celého systému je ovlivněn jeho plánovaným nasazením v rámci skenování interiérů historických budov. Funkčnost navrženého systému je nejprve otestována v rámci početných simulací a následně během experimentu s reálnými bezpilotními helikoptérami.This thesis is aimed at development of the system for safe autonomous survey of historical building interiors by the cooperative formation of multi-rotor unmanned aerial vehicles (UAVs). The proposed solution involves the method for safe trajectory tracking based on the leader-follower scheme and model predictive control, detection of potential faults and failures, and the mission controller which ensures the control of cooperation of particular UAVs and proper reaction on occurrence of faults and failures. The proposition of the whole system is influenced by the aim at its deployment in real world scenarios motivated by the documentation of historical monuments. The developed system is firstly evaluated in simulations. After that, it is tested in a real world scenario with the real UAVs
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