1,337 research outputs found
Instantaneous Momentum-Based Control of Floating Base Systems
In the last two decades a growing number of robotic applications such as autonomous drones, wheeled robots and industrial manipulators started to be employed in several human environments. However, these machines often possess limited locomotion and/or manipulation capabilities, thus reducing the number of achievable tasks and increasing the complexity of robot-environment interaction. Augmenting robots locomotion and manipulation abilities is a fundamental research topic, with a view to enhance robots participation in complex tasks involving safe interaction and cooperation with humans. To this purpose, humanoid robots, aerial manipulators and the novel design of flying humanoid robots are among the most promising platforms researchers are studying in the attempt to remove the existing technological barriers. These robots are often modeled as floating base systems, and have lost the assumption -- typical of fixed base robots -- of having one link always attached to the ground.
From the robot control side, contact forces regulation revealed to be fundamental for the execution of interaction tasks. Contact forces can be influenced by directly controlling the robot's momentum rate of change, and this fact gives rise to several momentum-based control strategies. Nevertheless, effective design of force and torque controllers still remains a complex challenge. The variability of sensor load during interaction, the inaccuracy of the force/torque sensing technology and the inherent nonlinearities of robot models are only a few complexities impairing efficient robot force control.
This research project focuses on the design of balancing and flight controllers for floating base robots interacting with the surrounding environment. More specifically, the research is built upon the state-of-the-art of momentum-based controllers and applied to three robotic platforms: the humanoid robot iCub, the aerial manipulator OTHex and the jet-powered humanoid robot iRonCub. The project enforces the existing literature with both theoretical and experimental results, aimed at achieving high robot performances and improved stability and robustness, in presence of different physical robot-environment interactions
Full-Body Torque-Level Non-linear Model Predictive Control for Aerial Manipulation
Non-linear model predictive control (nMPC) is a powerful approach to control
complex robots (such as humanoids, quadrupeds, or unmanned aerial manipulators
(UAMs)) as it brings important advantages over other existing techniques. The
full-body dynamics, along with the prediction capability of the optimal control
problem (OCP) solved at the core of the controller, allows to actuate the robot
in line with its dynamics. This fact enhances the robot capabilities and
allows, e.g., to perform intricate maneuvers at high dynamics while optimizing
the amount of energy used. Despite the many similarities between humanoids or
quadrupeds and UAMs, full-body torque-level nMPC has rarely been applied to
UAMs.
This paper provides a thorough description of how to use such techniques in
the field of aerial manipulation. We give a detailed explanation of the
different parts involved in the OCP, from the UAM dynamical model to the
residuals in the cost function. We develop and compare three different nMPC
controllers: Weighted MPC, Rail MPC, and Carrot MPC, which differ on the
structure of their OCPs and on how these are updated at every time step. To
validate the proposed framework, we present a wide variety of simulated case
studies. First, we evaluate the trajectory generation problem, i.e., optimal
control problems solved offline, involving different kinds of motions (e.g.,
aggressive maneuvers or contact locomotion) for different types of UAMs. Then,
we assess the performance of the three nMPC controllers, i.e., closed-loop
controllers solved online, through a variety of realistic simulations. For the
benefit of the community, we have made available the source code related to
this work.Comment: Submitted to Transactions on Robotics. 17 pages, 16 figure
Aerial Robotics for Inspection and Maintenance
Aerial robots with perception, navigation, and manipulation capabilities are extending the range of applications of drones, allowing the integration of different sensor devices and robotic manipulators to perform inspection and maintenance operations on infrastructures such as power lines, bridges, viaducts, or walls, involving typically physical interactions on flight. New research and technological challenges arise from applications demanding the benefits of aerial robots, particularly in outdoor environments. This book collects eleven papers from different research groups from Spain, Croatia, Italy, Japan, the USA, the Netherlands, and Denmark, focused on the design, development, and experimental validation of methods and technologies for inspection and maintenance using aerial robots
Decentralized Adaptive Control for Collaborative Manipulation of Rigid Bodies
In this work, we consider a group of robots working together to manipulate a
rigid object to track a desired trajectory in . The robots do not know
the mass or friction properties of the object, or where they are attached to
the object. They can, however, access a common state measurement, either from
one robot broadcasting its measurements to the team, or by all robots
communicating and averaging their state measurements to estimate the state of
their centroid. To solve this problem, we propose a decentralized adaptive
control scheme wherein each agent maintains and adapts its own estimate of the
object parameters in order to track a reference trajectory. We present an
analysis of the controller's behavior, and show that all closed-loop signals
remain bounded, and that the system trajectory will almost always (except for
initial conditions on a set of measure zero) converge to the desired
trajectory. We study the proposed controller's performance using numerical
simulations of a manipulation task in 3D, as well as hardware experiments which
demonstrate our algorithm on a planar manipulation task. These studies, taken
together, demonstrate the effectiveness of the proposed controller even in the
presence of numerous unmodeled effects, such as discretization errors and
complex frictional interactions
A Contribution to the Design of Highly Redundant Compliant Aerial Manipulation Systems
Es ist vorhersehbar, dass die Luftmanipulatoren in den nächsten Jahrzehnten für viele Aufgaben eingesetzt werden, die entweder zu gefährlich oder zu teuer sind, um sie mit herkömmlichen Methoden zu bewältigen. In dieser Arbeit wird eine neuartige Lösung für die Gesamtsteuerung von hochredundanten Luftmanipulationssystemen vorgestellt. Die Ergebnisse werden auf eine Referenzkonfiguration angewendet, die als universelle Plattform für die Durchführung verschiedener Luftmanipulationsaufgaben etabliert wird. Diese Plattform besteht aus einer omnidirektionalen Drohne und einem seriellen Manipulator. Um den modularen Regelungsentwurf zu gewährleisten, werden zwei rechnerisch effiziente Algorithmen untersucht, um den virtuellen Eingang den Aktuatorbefehlen zuzuordnen. Durch die Integration eines auf einem künstlichen neuronalen Netz basierenden Diagnosemoduls und der rekonfigurierbaren Steuerungszuordnung in den Regelkreis, wird die Fehlertoleranz für die Drohne erzielt. Außerdem wird die Motorsättigung durch Rekonfiguration der Geschwindigkeits- und Beschleunigungsprofile behandelt. Für die Beobachtung der externen Kräfte und Drehmomente werden zwei Filter vorgestellt. Dies ist notwendig, um ein nachgiebiges Verhalten des Endeffektors durch die achsenselektive Impedanzregelung zu erreichen. Unter Ausnutzung der Redundanz des vorgestellten Luftmanipulators wird ein Regler entworfen, der nicht nur die Referenz der Endeffektor-Bewegung verfolgt, sondern auch priorisierte sekundäre Aufgaben ausführt. Die Wirksamkeit der vorgestellten Lösungen wird durch umfangreiche Tests überprüft, und das vorgestellte Steuerungssystem wird als sehr vielseitig und effektiv bewertet.:1 Introduction
2 Fundamentals
3 System Design and Modeling
4 Reconfigurable Control Allocation
5 Fault Diagnostics For Free Flight
6 Force and Torque Observer
7 Trajectory Generation
8 Hybrid Task Priority Control
9 System Integration and Performance Evaluation
10 ConclusionIn the following decades, aerial manipulators are expected to be deployed in scenarios that are either too dangerous for human beings or too expensive to be accomplished by traditional methods. This thesis presents a novel solution for the overall control of highly redundant aerial manipulation systems. The results are applied to a reference configuration established as a universal platform for performing various aerial manipulation tasks. The platform consists of an omnidirectional multirotor UAV and a serial manipulator. To ensure modular control design, two computationally efficient algorithms are studied to allocate the virtual input to actuator commands. Fault tolerance of the aerial vehicle is achieved by integrating a diagnostic module based on an artificial neural network and the reconfigurable control allocation into the control loop. Besides, the risk of input saturation of individual rotors is minimized by predicting and reconfiguring the speed and acceleration responses. Two filter-based observers are presented to provide the knowledge of external forces and torques, which is necessary to achieve compliant behavior of the end-effector through an axis-selective impedance control in the outer loop. Exploiting the redundancy of the proposed aerial manipulator, the author has designed a control law to achieve the desired end-effector motion and execute secondary tasks in order of priority. The effectiveness of the proposed designs is verified with extensive tests generated by following Monte Carlo method, and the presented control scheme is proved to be versatile and effective.:1 Introduction
2 Fundamentals
3 System Design and Modeling
4 Reconfigurable Control Allocation
5 Fault Diagnostics For Free Flight
6 Force and Torque Observer
7 Trajectory Generation
8 Hybrid Task Priority Control
9 System Integration and Performance Evaluation
10 Conclusio
Nonlinear Control Strategies for Outdoor Aerial Manipulators
In this thesis, the design, validation and implementation of nonlinear control strategies for aerial manipulators
{i.e. aerial robots equipped with manipulators{ is studied, with special emphasis on the internal coupling of the
system and its resilience against external disturbances. For the rst, di erent decentralised control strategies
{i.e. using di erent control typologies for each one of the subsystems{ that indirectly take into account this
coupling have been analysed. As a result, a nonlinear strategy composed of two controllers is proposed. A higher
priority is given to the manipulation accuracy, relaxing the platform tracking, and hence obtaining a solution
improving the manipulation capabilities with the surrounding environment. To validate these results, thorough
stability and robustness analyses are provided, both theoretically and in simulation.
On the other hand, a signi cant e ort has been devoted to improving the response and applicability of
robot manipulators used in
ight via control. In particular, the design of controllers for lightweight
exible
manipulators {that reduce the consequences of incidents involving unforeseen contacts{ is analysed. Although
their inherent nature perfectly ts for aerial manipulation applications, the added
exibility produces unwanted
behaviours, such as second-order modes and uncertainties. To cope with them, an adaptable position nonlinear
control strategy is proposed. To validate this contribution, the stability of the approach is studied in theory
and its capabilities are proven in several experimental scenarios. In these, the robustness of the solution against
unforeseen impacts and contact with uncharacterised interfaces is demonstrated.
Subsequently, this strategy has been enriched with {multiaxis{ force control capabilities thanks to the
inclusion of an outer control loop modifying the manipulator reference. Accordingly, this additional applicationfocused
capability is added to the controlled system without loosing the modulated response of the inner-loop
position strategy. It is also worth noting that, thanks to the cascade-like nature of the modi cation, the transition
between position and force control modes is inherently smooth and automatic. The stability of this expanded
strategy has been theoretically analysed and the results validated in a set of experimental scenarios.
To validate the rst nonlinear approach with realistic outdoor simulations before its implementation, a
computational
uid dynamics analysis has been performed to obtain an explicit model of the aerodynamic
forces and torques applied to the blunt-body of the aerial platform in
ight. The results of this study have been
compared to the most common alternative nowadays, being highlighted that the proposed model signi cantly
surpasses this option in terms of accuracy. Moreover, it is worth underscoring that this characterisation could
be also employed in the future to develop control solutions with enhanced rejection capabilities against wind
conditions.
Finally, as the focus of this thesis is on the use of novel control strategies on real aerial manipulation outdoors
to improve their accuracy while performing complex tasks, a modular autopilot solution to be able to implement
them has been also developed. This general-purpose autopilot allows the implementation of new algorithms,
and facilitates their theory-to-experimentation transition. Taking into account this perspective, the proposed
tool employs the simple and widely-known MAS interface and the highly reliable PX4 autopilot as backup, thus
providing a redundant approach to handle unexpected incidents in
ight.En esta tesis se ha estudiado el diseño, validación e implementación de estrategias de control
no lineales para robots manipuladores aéreos –esto es, robots aéreos equipados con un sistema
de manipulación robótica–, dándose especial énfasis a las interacciones internas del sistema y a
su resiliencia frente a efectos externos. Para lo primero, se han analizado diferentes estrategias
de control descentralizado –es decir, que usan tipologías de control diferentes para cada uno de
los subsistemas–, pero que tienen indirectamente en consideración la interacción entre manipulación
y vuelo. Como resultado de esta línea, se propone una estretegia de control conformada
por dos controladores. Estos se coordinan de tal forma que se le da prioridad a la manipulación
sobre el seguimiento de posiciones del vehículo, produciéndose un sistema de control que mejora
la precisión de las interacciones entre el sistema manipulador y el entorno. Para validar estos resultados,
se ha analizado su estabilidad y robustez tanto teóricamente como mediante simulaciones
numéricas.
Por otro lado, se ha buscado mejorar la respuesta y aplicabilidad de los manipuladores que se
usan en vuelo mediante su control. Dentro de esta tendencia, la tesis se ha centrado en el diseño
de controladores para manipuladores ligeros flexibles, ya que estos permiten reducir el peso del
sistema completo y reducen el riesgo de incidentes debidos a contactos inesperados. Sin embargo,
la flexibilidad de estos produce comportamientos indeseados durante la operación, como la aparición
de modos de segundo orden y cierta incentidumbre en su comportamiento. Para reducir su
impacto en la precisión de las tareas de manipulación, se ha desarrollado un controlador no lineal
adaptable. Para validar estos resultados, se ha analizado la estabilidad del sistema teóricamente y se
han desarrollado una serie de experimentos. En ellos, se ha comprobado su robustez ante impactos
inesperados y contactos con elementos no caracterizados.
Posteriormente, esta estrategia para manipuladores flexibles ha sido ampliada al añadir un bucle
externo que posibilita el control en fuerzas en varias direcciones. Esto permite, mediante un único
controlador, mantener la suave respuesta de la estrategia. Además cabe destacar que, al contar esta
estrategia con un diseño en cascade, la transición entre los segmentos de desplazamiento del brazo
y de aplicación de fuerzas es fluida y automática. La estabilidad de esta estrategia ampliada ha sido
analizada teóricamente y los resultados han sido validados experimentalmente.
Para validar la primera estrategia mediante simulaciones que representen fielmente las condiciones
en exteriores antes de su implementación, ha sido necesario realizar un estudio mediante
mecánica de fluidos computacional para obtener un modelo explícito de las fuerzas y momentos
aerodinámicos a los que se efrenta la plataforma en vuelo. Los resultados de este estudio han
sido comparados con la alternativa más empleada actualmente, mostrándose que los avances del
método propuesto son sustanciales. Asimismo, es importante destacar que esta caracterización podría
también usarse en el futuro para desarrollar controladores con una respuesta mejorada ante
perturbaciones aerodinámicas, como en el caso de volar con viento. Finalmente, al ser esta una tesis centrada en las estrategias de control novedosas en sistemas
reales para la mejora de su rendimiento en misiones complejas, se ha desarrollado un autopiloto
modular fácilmente modificable para implementarlas. Este permite validar experimentalmente
nuevos algoritmos y facilita la transición entre teoría y práctica. Para ello, esta herramienta se
basa en una interfaz sencilla ampliamente conocida por los investigadores de robótica, Simulink®,
y cuenta con un autopiloto de respaldo, PX4, para enfrentarse a los incidentes inesperados que
pudieran surgir en vuelo
A Survey on Aerial Swarm Robotics
The use of aerial swarms to solve real-world problems has been increasing steadily, accompanied by falling prices and improving performance of communication, sensing, and processing hardware. The commoditization of hardware has reduced unit costs, thereby lowering the barriers to entry to the field of aerial swarm robotics. A key enabling technology for swarms is the family of algorithms that allow the individual members of the swarm to communicate and allocate tasks amongst themselves, plan their trajectories, and coordinate their flight in such a way that the overall objectives of the swarm are achieved efficiently. These algorithms, often organized in a hierarchical fashion, endow the swarm with autonomy at every level, and the role of a human operator can be reduced, in principle, to interactions at a higher level without direct intervention. This technology depends on the clever and innovative application of theoretical tools from control and estimation. This paper reviews the state of the art of these theoretical tools, specifically focusing on how they have been developed for, and applied to, aerial swarms. Aerial swarms differ from swarms of ground-based vehicles in two respects: they operate in a three-dimensional space and the dynamics of individual vehicles adds an extra layer of complexity. We review dynamic modeling and conditions for stability and controllability that are essential in order to achieve cooperative flight and distributed sensing. The main sections of this paper focus on major results covering trajectory generation, task allocation, adversarial control, distributed sensing, monitoring, and mapping. Wherever possible, we indicate how the physics and subsystem technologies of aerial robots are brought to bear on these individual areas
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