43 research outputs found
Enabling Communication Technologies for Automated Unmanned Vehicles in Industry 4.0
Within the context of Industry 4.0, mobile robot systems such as automated
guided vehicles (AGVs) and unmanned aerial vehicles (UAVs) are one of the major
areas challenging current communication and localization technologies. Due to
stringent requirements on latency and reliability, several of the existing
solutions are not capable of meeting the performance required by industrial
automation applications. Additionally, the disparity in types and applications
of unmanned vehicle (UV) calls for more flexible communication technologies in
order to address their specific requirements. In this paper, we propose several
use cases for UVs within the context of Industry 4.0 and consider their
respective requirements. We also identify wireless technologies that support
the deployment of UVs as envisioned in Industry 4.0 scenarios.Comment: 7 pages, 1 figure, 1 tabl
Towards Collaborative Simultaneous Localization and Mapping: a Survey of the Current Research Landscape
Motivated by the tremendous progress we witnessed in recent years, this paper
presents a survey of the scientific literature on the topic of Collaborative
Simultaneous Localization and Mapping (C-SLAM), also known as multi-robot SLAM.
With fleets of self-driving cars on the horizon and the rise of multi-robot
systems in industrial applications, we believe that Collaborative SLAM will
soon become a cornerstone of future robotic applications. In this survey, we
introduce the basic concepts of C-SLAM and present a thorough literature
review. We also outline the major challenges and limitations of C-SLAM in terms
of robustness, communication, and resource management. We conclude by exploring
the area's current trends and promising research avenues.Comment: 44 pages, 3 figure
Emerging research directions in computer science : contributions from the young informatics faculty in Karlsruhe
In order to build better human-friendly human-computer interfaces,
such interfaces need to be enabled with capabilities to perceive
the user, his location, identity, activities and in particular his interaction
with others and the machine. Only with these perception capabilities
can smart systems ( for example human-friendly robots or smart environments) become posssible. In my research I\u27m thus focusing on the
development of novel techniques for the visual perception of humans and
their activities, in order to facilitate perceptive multimodal interfaces,
humanoid robots and smart environments. My work includes research
on person tracking, person identication, recognition of pointing gestures,
estimation of head orientation and focus of attention, as well as
audio-visual scene and activity analysis. Application areas are humanfriendly
humanoid robots, smart environments, content-based image and
video analysis, as well as safety- and security-related applications. This
article gives a brief overview of my ongoing research activities in these
areas
Bio-Inspired Robotics
Modern robotic technologies have enabled robots to operate in a variety of unstructured and dynamically-changing environments, in addition to traditional structured environments. Robots have, thus, become an important element in our everyday lives. One key approach to develop such intelligent and autonomous robots is to draw inspiration from biological systems. Biological structure, mechanisms, and underlying principles have the potential to provide new ideas to support the improvement of conventional robotic designs and control. Such biological principles usually originate from animal or even plant models, for robots, which can sense, think, walk, swim, crawl, jump or even fly. Thus, it is believed that these bio-inspired methods are becoming increasingly important in the face of complex applications. Bio-inspired robotics is leading to the study of innovative structures and computing with sensory–motor coordination and learning to achieve intelligence, flexibility, stability, and adaptation for emergent robotic applications, such as manipulation, learning, and control. This Special Issue invites original papers of innovative ideas and concepts, new discoveries and improvements, and novel applications and business models relevant to the selected topics of ``Bio-Inspired Robotics''. Bio-Inspired Robotics is a broad topic and an ongoing expanding field. This Special Issue collates 30 papers that address some of the important challenges and opportunities in this broad and expanding field
XLIII Jornadas de Automática: libro de actas: 7, 8 y 9 de septiembre de 2022, Logroño (La Rioja)
[Resumen] Las Jornadas de Automática (JA) son el evento más importante del Comité Español de Automática (CEA), entidad científico-técnica con más de cincuenta años de vida y destinada a la difusión e implantación de la Automática en la sociedad. Este año se celebra la cuadragésima tercera edición de las JA, que constituyen el punto de encuentro de la comunidad de Automática de nuestro país. La presente edición permitirá dar visibilidad a los nuevos retos y resultados del ámbito, y su uso en un gran número de aplicaciones, entre otras, las energías renovables, la bioingeniería o la robótica asistencial. Además de la componente científica, que se ve reflejada en este libro de actas, las JA son un punto de encuentro de las diferentes generaciones de profesores, investigadores y profesionales, incluyendo la componente social que es de vital importancia.
Esta edición 2022 de las JA se celebra en Logroño, capital de La Rioja, región mundialmente conocida por la calidad de sus vinos de Denominación de Origen y que ha asumido el desafío de poder ganar competitividad a través de la transformación verde y digital. Pero también por ser la cuna del castellano e impulsar el Valle de la Lengua con la ayuda de las nuevas tecnologías, entre ellas la Automática Inteligente. Los organizadores de estas JA, pertenecientes al Área de Ingeniería de Sistemas y Automática del Departamento de Ingeniería Eléctrica de la Universidad de La Rioja (UR), constituyen un pilar fundamental en el apoyo a la región para el estudio, implementación y difusión de estos retos.
Esta edición, la primera en formato íntegramente presencial después de la pandemia de la covid-19, cuenta con más de 200 asistentes y se celebra a caballo entre el Edificio Politécnico de la Escuela Técnica Superior de Ingeniería Industrial y el Monasterio de Yuso situado en San Millán de la Cogolla, dos marcos excepcionales para la realización de las JA. Como parte del programa científico, dos sesiones plenarias harán hincapié, respectivamente, sobre soluciones de control para afrontar los nuevos retos energéticos, y sobre la calidad de los datos para una inteligencia artificial (IA) imparcial y confiable. También, dos mesas redondas debatirán aplicaciones de la IA y la implantación de la tecnología digital en la actividad profesional. Adicionalmente, destacaremos dos clases magistrales alineadas con tecnología de última generación que serán impartidas por profesionales de la empresa. Las JA también van a albergar dos competiciones: CEABOT, con robots humanoides, y el Concurso de Ingeniería de Control, enfocado a UAVs. A todas estas actividades hay que añadir las reuniones de los grupos temáticos de CEA, las exhibiciones de pósteres con las comunicaciones presentadas a las JA y los expositores de las empresas. Por último, durante el evento se va a proceder a la entrega del “Premio Nacional de Automática” (edición 2022) y del “Premio CEA al Talento Femenino en Automática”, patrocinado por el Gobierno de La Rioja (en su primera edición), además de diversos galardones enmarcados dentro de las actividades de los grupos temáticos de CEA.
Las actas de las XLIII Jornadas de Automática están formadas por un total de 143 comunicaciones, organizadas en torno a los nueve Grupos Temáticos y a las dos Líneas Estratégicas de CEA. Los trabajos seleccionados han sido sometidos a un proceso de revisión por pares
Multimodal Navigation for Accurate Space Rendezvous Missions
© Cranfield University 2021. All rights reserved. No part of
this publication may be reproduced without the written
permission of the copyright ownerRelative navigation is paramount in space missions that involve rendezvousing
between two spacecraft. It demands accurate and continuous estimation of the six
degree-of-freedom relative pose, as this stage involves close-proximity-fast-reaction
operations that can last up to five orbits. This has been routinely achieved thanks to
active sensors such as lidar, but their large size, cost, power and limited operational
range remain a stumbling block for en masse on-board integration. With the onset
of faster processing units, lighter and cheaper passive optical sensors are emerging as
the suitable alternative for autonomous rendezvous in combination with computer
vision algorithms. Current vision-based solutions, however, are limited by adverse
illumination conditions such as solar glare, shadowing, and eclipse. These effects are
exacerbated when the target does not hold cooperative markers to accommodate the
estimation process and is incapable of controlling its rotational state.
This thesis explores novel model-based methods that exploit sequences of monoc ular images acquired by an on-board camera to accurately carry out spacecraft
relative pose estimation for non-cooperative close-range rendezvous with a known
artificial target. The proposed solutions tackle the current challenges of imaging in
the visible spectrum and investigate the contribution of the long wavelength infrared
(or “thermal”) band towards a combined multimodal approach.
As part of the research, a visible-thermal synthetic dataset of a rendezvous
approach with the defunct satellite Envisat is generated from the ground up using a
realistic orbital camera simulator. From the rendered trajectories, the performance
of several state-of-the-art feature detectors and descriptors is first evaluated for
both modalities in a tailored scenario for short and wide baseline image processing
transforms. Multiple combinations, including the pairing of algorithms with their
non-native counterparts, are tested. Computational runtimes are assessed in an
embedded hardware board.
From the insight gained, a method to estimate the pose on the visible band is
derived from minimising geometric constraints between online local point and edge
contour features matched to keyframes generated offline from a 3D model of the
target. The combination of both feature types is demonstrated to achieve a pose
solution for a tumbling target using a sparse set of training images, bypassing the
need for hardware-accelerated real-time renderings of the model.
The proposed algorithm is then augmented with an extended Kalman filter
which processes each feature-induced minimisation output as individual pseudo measurements, fusing them to estimate the relative pose and velocity states at
each time-step. Both the minimisation and filtering are established using Lie group
formalisms, allowing for the covariance of the solution computed by the former to be automatically incorporated as measurement noise in the latter, providing
an automatic weighing of each feature type directly related to the quality of the
matches. The predicted states are then used to search for new feature matches in the
subsequent time-step. Furthermore, a method to derive a coarse viewpoint estimate
to initialise the nominal algorithm is developed based on probabilistic modelling of
the target’s shape. The robustness of the complete approach is demonstrated for
several synthetic and laboratory test cases involving two types of target undergoing
extreme illumination conditions.
Lastly, an innovative deep learning-based framework is developed by processing
the features extracted by a convolutional front-end with long short-term memory cells,
thus proposing the first deep recurrent convolutional neural network for spacecraft
pose estimation. The framework is used to compare the performance achieved by
visible-only and multimodal input sequences, where the addition of the thermal band
is shown to greatly improve the performance during sunlit sequences. Potential
limitations of this modality are also identified, such as when the target’s thermal
signature is comparable to Earth’s during eclipse.PH