1,858 research outputs found
Image-based visual servo control of the translation kinematics of a quadrotor aerial vehicle
International audienceIn this paper, we investigate a range of image-based visual servo control algorithms for regulation of the position of a quadrotor aerial vehicle. The most promising control algorithms have been successfully implemented on an autonomous aerial vehicle and demonstrate excellent performance
Image-based Visual Servo Control for Aerial Manipulation Using a Fully-Actuated UAV
Using Unmanned Aerial Vehicles (UAVs) to perform high-altitude manipulation
tasks beyond just passive visual application can reduce the time, cost, and
risk of human workers. Prior research on aerial manipulation has relied on
either ground truth state estimate or GPS/total station with some Simultaneous
Localization and Mapping (SLAM) algorithms, which may not be practical for many
applications close to infrastructure with degraded GPS signal or featureless
environments. Visual servo can avoid the need to estimate robot pose. Existing
works on visual servo for aerial manipulation either address solely
end-effector position control or rely on precise velocity measurement and
pre-defined visual visual marker with known pattern. Furthermore, most of
previous work used under-actuated UAVs, resulting in complicated mechanical and
hence control design for the end-effector. This paper develops an image-based
visual servo control strategy for bridge maintenance using a fully-actuated
UAV. The main components are (1) a visual line detection and tracking system,
(2) a hybrid impedance force and motion control system. Our approach does not
rely on either robot pose/velocity estimation from an external localization
system or pre-defined visual markers. The complexity of the mechanical system
and controller architecture is also minimized due to the fully-actuated nature.
Experiments show that the system can effectively execute motion tracking and
force holding using only the visual guidance for the bridge painting. To the
best of our knowledge, this is one of the first studies on aerial manipulation
using visual servo that is capable of achieving both motion and force control
without the need of external pose/velocity information or pre-defined visual
guidance.Comment: Accepted by 2023 IEEE/RSJ International Conference on Intelligent
Robots and Systems (IROS
Effective Target Aware Visual Navigation for UAVs
In this paper we propose an effective vision-based navigation method that
allows a multirotor vehicle to simultaneously reach a desired goal pose in the
environment while constantly facing a target object or landmark. Standard
techniques such as Position-Based Visual Servoing (PBVS) and Image-Based Visual
Servoing (IBVS) in some cases (e.g., while the multirotor is performing fast
maneuvers) do not allow to constantly maintain the line of sight with a target
of interest. Instead, we compute the optimal trajectory by solving a non-linear
optimization problem that minimizes the target re-projection error while
meeting the UAV's dynamic constraints. The desired trajectory is then tracked
by means of a real-time Non-linear Model Predictive Controller (NMPC): this
implicitly allows the multirotor to satisfy both the required constraints. We
successfully evaluate the proposed approach in many real and simulated
experiments, making an exhaustive comparison with a standard approach.Comment: Conference paper at "European Conference on Mobile Robotics" (ECMR)
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Visual guidance of unmanned aerial manipulators
The ability to fly has greatly expanded the possibilities for robots to perform surveillance, inspection or map generation tasks. Yet it was only in recent years that research in aerial robotics was mature enough to allow active interactions with the environment. The robots responsible for these interactions are called aerial manipulators and usually combine a multirotor platform and one or more robotic arms.
The main objective of this thesis is to formalize the concept of aerial manipulator and present guidance methods, using visual information, to provide them with autonomous functionalities.
A key competence to control an aerial manipulator is the ability to localize it in the environment.
Traditionally, this localization has required external infrastructure of sensors (e.g., GPS or IR cameras), restricting the real applications. Furthermore, localization methods with on-board sensors, exported from other robotics fields such as simultaneous localization and mapping (SLAM), require large computational units becoming a handicap in vehicles where size, load,
and power consumption are important restrictions. In this regard, this thesis proposes a method to estimate the state of the vehicle (i.e., position, orientation, velocity and acceleration) by means of on-board, low-cost, light-weight and high-rate sensors.
With the physical complexity of these robots, it is required to use advanced control techniques during navigation. Thanks to their redundancy on degrees-of-freedom, they offer the possibility to accomplish not only with mobility requirements but with other tasks simultaneously and hierarchically, prioritizing them depending on their impact to the overall mission success. In this work we present such control laws and define a number of these tasks to drive the vehicle using visual information, guarantee the robot integrity during flight, and improve
the platform stability or increase arm operability.
The main contributions of this research work are threefold: (1) Present a localization technique to allow autonomous navigation, this method is specifically designed for aerial platforms with size, load and computational burden restrictions. (2) Obtain control commands to drive the vehicle using visual information (visual servo). (3) Integrate the visual servo commands into
a hierarchical control law by exploiting the redundancy of the robot to accomplish secondary tasks during flight. These tasks are specific for aerial manipulators and they are also provided.
All the techniques presented in this document have been validated throughout extensive experimentation with real robotic platforms.La capacitat de volar ha incrementat molt les possibilitats dels robots per a realitzar tasques de vigilància, inspecció o generació de mapes. Tot i això, no és fins fa pocs anys que la recerca en robòtica aèria ha estat prou madura com per començar a permetre interaccions amb l’entorn d’una manera activa. Els robots per a fer-ho s’anomenen manipuladors aeris i habitualment combinen una plataforma multirotor i un braç robòtic.
L’objectiu d’aquesta tesi és formalitzar el concepte de manipulador aeri i presentar mètodes de guiatge, utilitzant informació visual, per dotar d’autonomia aquest tipus de vehicles.
Una competència clau per controlar un manipulador aeri és la capacitat de localitzar-se en l’entorn. Tradicionalment aquesta localització ha requerit d’infraestructura sensorial externa (GPS, càmeres IR, etc.), limitant així les aplicacions reals. Pel contrari, sistemes de localització exportats d’altres camps de la robòtica basats en sensors a bord, com per exemple mètodes de localització i mapejat simultànis (SLAM), requereixen de gran capacitat de còmput, característica que penalitza molt en vehicles on la mida, pes i consum elèctric son grans restriccions. En aquest sentit, aquesta tesi proposa un mètode d’estimació d’estat del robot (posició, velocitat, orientació i acceleració) a partir de sensors instal·lats a bord, de baix cost, baix consum computacional i que proporcionen mesures a alta freqüència.
Degut a la complexitat física d’aquests robots, és necessari l’ús de tècniques de control avançades. Gràcies a la seva redundància de graus de llibertat, aquests robots ens ofereixen la possibilitat de complir amb els requeriments de mobilitat i, simultàniament, realitzar tasques de manera jeràrquica, ordenant-les segons l’impacte en l’acompliment de la missió. En aquest treball es presenten aquestes lleis de control, juntament amb la descripció de tasques per tal de guiar visualment el vehicle, garantir la integritat del robot durant el vol, millorar de l’estabilitat del vehicle o augmentar la manipulabilitat del braç.
Aquesta tesi es centra en tres aspectes fonamentals: (1) Presentar una tècnica de localització per dotar d’autonomia el robot. Aquest mètode està especialment dissenyat per a plataformes amb restriccions de capacitat computacional, mida i pes. (2) Obtenir les comandes de control necessàries per guiar el vehicle a partir d’informació visual. (3) Integrar aquestes accions dins una estructura de control jeràrquica utilitzant la redundància del robot per complir altres tasques durant el vol. Aquestes tasques son específiques per a manipuladors aeris i també es defineixen en aquest document.
Totes les tècniques presentades en aquesta tesi han estat avaluades de manera experimental amb plataformes robòtiques real
Kinematic Visual Servo Control of a Quadrotor aerial vehicle
Visual systems are key sensors for control of small scale unmanned aerial vehicles. In this paper we investigate a range of image based visual servo control algorithms for positioning of flying vehicles capable of hover. The image based outer control loop for translation kinematics is coupled to a high-gain inner control loop that regulates translational velocities and full attitude dynamics. Zero and first order image moments are used as visual features for the control design. Perspective projection moments with suitable scaling along with a classical image based visual servo control design lead to satisfactory transients and asymptotic stability of the closed-loop system when the image plane remains parallel to the target. However, the system response may lack robustness for aggressive manoeuvres. In order to overcome this problem, several control schemes, based on spherical image moments, are designed and their performance is analysed. All designed control laws have been tested on a kinematic robotic manipulator to demonstrate the relative strengths and weaknesses of thedifferent image based visual servo control designs. The three most promising control algorithms have been successfully implemented on an autonomous aerial vehicle showing excellent performances in all three cases
Asymptotic Vision-Based Tracking Control of the Quadrotor Aerial Vehicle
This paper proposes an image-based visual servo (IBVS) controller for the 3D translational
motion of the quadrotor unmanned aerial vehicle (UAV). The main purpose of this paper is to
provide asymptotic stability for vision-based tracking control of the quadrotor in the presence
of uncertainty in the dynamic model of the system. The aim of the paper also includes the use
of
ow of image features as the velocity information to compensate for the unreliable linear
velocity data measured by accelerometers. For this purpose, the mathematical model of the
quadrotor is presented based on the optic
ow of image features which provides the possibility
of designing a velocity-free IBVS controller with considering the dynamics of the robot. The
image features are de ned from a suitable combination of perspective image moments without
using the model of the object. This property allows the application of the proposed controller
in unknown places. The controller is robust with respect to the uncertainties in the transla-
tional dynamics of the system associated with the target motion, image depth and external
disturbances. Simulation results and a comparison study are presented which demonstrate the
e ectiveness of the proposed approach
A low-cost vision-based unmanned aerial system for extremely low-light GPS-denied navigation and thermal imaging
A Low-Cost Vision-Based Unmanned Aerial System for Extremely Low-Light GPS-Denied Navigation and Thermal Imaging}, abstract = {This paper presents the design and implementation details of a complete unmanned aerial system (UAS) based on commercial-off-the-shelf (COTS) components, focusing on safety, security, search and rescue scenarios in GPS-denied environments. In particular, the aerial platform is capable of semi-autonomously navigating through extremely low-light, GPS-denied indoor environments based on onboard sensors only, including a downward-facing optical flow camera. Besides, an additional low-cost payload camera system is developed to stream both infrared video and visible light video to a ground station in real-time, for the purpose of detecting sign of life and hidden humans. The total cost of the complete system is estimated to be $1150, and the effectiveness of the system has been tested and validated in practical scenarios
Asymptotic Vision-Based Tracking Control of the Quadrotor Aerial Vehicle
This paper proposes an image-based visual servo (IBVS) controller for the 3D translational
motion of the quadrotor unmanned aerial vehicle (UAV). The main purpose of this paper is to
provide asymptotic stability for vision-based tracking control of the quadrotor in the presence
of uncertainty in the dynamic model of the system. The aim of the paper also includes the use
of
ow of image features as the velocity information to compensate for the unreliable linear
velocity data measured by accelerometers. For this purpose, the mathematical model of the
quadrotor is presented based on the optic
ow of image features which provides the possibility
of designing a velocity-free IBVS controller with considering the dynamics of the robot. The
image features are de ned from a suitable combination of perspective image moments without
using the model of the object. This property allows the application of the proposed controller
in unknown places. The controller is robust with respect to the uncertainties in the transla-
tional dynamics of the system associated with the target motion, image depth and external
disturbances. Simulation results and a comparison study are presented which demonstrate the
e ectiveness of the proposed approach
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