Multi-task near-field perception for autonomous driving using surround-view fisheye cameras

Die Bildung der Augen führte zum Urknall der Evolution. Die Dynamik änderte sich von einem primitiven Organismus, der auf den Kontakt mit der Nahrung wartete, zu einem Organismus, der durch visuelle Sensoren gesucht wurde. Das menschliche Auge ist eine der raffiniertesten Entwicklungen der Evolution, aber es hat immer noch Mängel. Der Mensch hat über Millionen von Jahren einen biologischen Wahrnehmungsalgorithmus entwickelt, der in der Lage ist, Autos zu fahren, Maschinen zu bedienen, Flugzeuge zu steuern und Schiffe zu navigieren. Die Automatisierung dieser Fähigkeiten für Computer ist entscheidend für verschiedene Anwendungen, darunter selbstfahrende Autos, Augmented Realität und architektonische Vermessung. Die visuelle Nahfeldwahrnehmung im Kontext von selbstfahrenden Autos kann die Umgebung in einem Bereich von 0 - 10 Metern und 360° Abdeckung um das Fahrzeug herum wahrnehmen. Sie ist eine entscheidende Entscheidungskomponente bei der Entwicklung eines sichereren automatisierten Fahrens. Jüngste Fortschritte im Bereich Computer Vision und Deep Learning in Verbindung mit hochwertigen Sensoren wie Kameras und LiDARs haben ausgereifte Lösungen für die visuelle Wahrnehmung hervorgebracht. Bisher stand die Fernfeldwahrnehmung im Vordergrund. Ein weiteres wichtiges Problem ist die begrenzte Rechenleistung, die für die Entwicklung von Echtzeit-Anwendungen zur Verfügung steht. Aufgrund dieses Engpasses kommt es häufig zu einem Kompromiss zwischen Leistung und Laufzeiteffizienz. Wir konzentrieren uns auf die folgenden Themen, um diese anzugehen: 1) Entwicklung von Nahfeld-Wahrnehmungsalgorithmen mit hoher Leistung und geringer Rechenkomplexität für verschiedene visuelle Wahrnehmungsaufgaben wie geometrische und semantische Aufgaben unter Verwendung von faltbaren neuronalen Netzen. 2) Verwendung von Multi-Task-Learning zur Überwindung von Rechenengpässen durch die gemeinsame Nutzung von initialen Faltungsschichten zwischen den Aufgaben und die Entwicklung von Optimierungsstrategien, die die Aufgaben ausbalancieren.The formation of eyes led to the big bang of evolution. The dynamics changed from a primitive organism waiting for the food to come into contact for eating food being sought after by visual sensors. The human eye is one of the most sophisticated developments of evolution, but it still has defects. Humans have evolved a biological perception algorithm capable of driving cars, operating machinery, piloting aircraft, and navigating ships over millions of years. Automating these capabilities for computers is critical for various applications, including self-driving cars, augmented reality, and architectural surveying. Near-field visual perception in the context of self-driving cars can perceive the environment in a range of 0 - 10 meters and 360° coverage around the vehicle. It is a critical decision-making component in the development of safer automated driving. Recent advances in computer vision and deep learning, in conjunction with high-quality sensors such as cameras and LiDARs, have fueled mature visual perception solutions. Until now, far-field perception has been the primary focus. Another significant issue is the limited processing power available for developing real-time applications. Because of this bottleneck, there is frequently a trade-off between performance and run-time efficiency. We concentrate on the following issues in order to address them: 1) Developing near-field perception algorithms with high performance and low computational complexity for various visual perception tasks such as geometric and semantic tasks using convolutional neural networks. 2) Using Multi-Task Learning to overcome computational bottlenecks by sharing initial convolutional layers between tasks and developing optimization strategies that balance tasks

Advances in Robot Navigation

Robot navigation includes different interrelated activities such as perception - obtaining and interpreting sensory information; exploration - the strategy that guides the robot to select the next direction to go; mapping - the construction of a spatial representation by using the sensory information perceived; localization - the strategy to estimate the robot position within the spatial map; path planning - the strategy to find a path towards a goal location being optimal or not; and path execution, where motor actions are determined and adapted to environmental changes. This book integrates results from the research work of authors all over the world, addressing the abovementioned activities and analyzing the critical implications of dealing with dynamic environments. Different solutions providing adaptive navigation are taken from nature inspiration, and diverse applications are described in the context of an important field of study: social robotics

Humanoid Robots

For many years, the human being has been trying, in all ways, to recreate the complex mechanisms that form the human body. Such task is extremely complicated and the results are not totally satisfactory. However, with increasing technological advances based on theoretical and experimental researches, man gets, in a way, to copy or to imitate some systems of the human body. These researches not only intended to create humanoid robots, great part of them constituting autonomous systems, but also, in some way, to offer a higher knowledge of the systems that form the human body, objectifying possible applications in the technology of rehabilitation of human beings, gathering in a whole studies related not only to Robotics, but also to Biomechanics, Biomimmetics, Cybernetics, among other areas. This book presents a series of researches inspired by this ideal, carried through by various researchers worldwide, looking for to analyze and to discuss diverse subjects related to humanoid robots. The presented contributions explore aspects about robotic hands, learning, language, vision and locomotion

MUSME 2011 4 th International Symposium on Multibody Systems and Mechatronics

El libro de actas recoge las aportaciones de los autores a través de los correspondientes artículos a la Dinámica de Sistemas Multicuerpo y la Mecatrónica (Musme). Estas disciplinas se han convertido en una importante herramienta para diseñar máquinas, analizar prototipos virtuales y realizar análisis CAD sobre complejos sistemas mecánicos articulados multicuerpo. La dinámica de sistemas multicuerpo comprende un gran número de aspectos que incluyen la mecánica, dinámica estructural, matemáticas aplicadas, métodos de control, ciencia de los ordenadores y mecatrónica. Los artículos recogidos en el libro de actas están relacionados con alguno de los siguientes tópicos del congreso: Análisis y síntesis de mecanismos ; Diseño de algoritmos para sistemas mecatrónicos ; Procedimientos de simulación y resultados ; Prototipos y rendimiento ; Robots y micromáquinas ; Validaciones experimentales ; Teoría de simulación mecatrónica ; Sistemas mecatrónicos ; Control de sistemas mecatrónicosUniversitat Politècnica de València (2011). MUSME 2011 4 th International Symposium on Multibody Systems and Mechatronics. Editorial Universitat Politècnica de València. http://hdl.handle.net/10251/13224Archivo delegad

Manipulador aéreo con brazos antropomórficos de articulaciones flexibles

[Resumen] Este artículo presenta el primer robot manipulador aéreo con dos brazos antropomórficos diseñado para aplicarse en tareas de inspección y mantenimiento en entornos industriales de difícil acceso para operarios humanos. El robot consiste en una plataforma aérea multirrotor equipada con dos brazos antropomórficos ultraligeros, así como el sistema de control integrado de la plataforma y los brazos. Una de las principales características del manipulador es la flexibilidad mecánica proporcionada en todas las articulaciones, lo que aumenta la seguridad en las interacciones físicas con el entorno y la protección del propio robot. Para ello se ha introducido un compacto y simple mecanismo de transmisión por muelle entre el eje del servo y el enlace de salida. La estructura en aluminio de los brazos ha sido cuidadosamente diseñada de forma que los actuadores estén aislados frente a cargas radiales y axiales que los puedan dañar. El manipulador desarrollado ha sido validado a través de experimentos en base fija y en pruebas de vuelo en exteriores.Ministerio de Economía y Competitividad; DPI2014-5983-C2-1-

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp