Safe Control of Manufacturing Vehicles Research Towards Standard Test Methods

The National Institute of Standards and Technology‟s Intelligent Systems Division has been researching several areas leading to safe control of manufacturing vehicles to improve automated guided vehicle (AGV) safety standards. The research areas include: AGV safety and control based on advanced two-dimensional (2D) sensors that detect moving standard test pieces representing humans; Ability of advanced 3D imaging sensors, when mounted to an AGV or forklift, to detect stationary or moving objects and test pieces on the ground or hanging over the work area; and Manned forklift safety based on advanced 3D imaging sensors that detect visible and non-visible regions for forklift operators. Experiments and results in the above areas are presented in this paper. The experimental results will be used to develop and recommend standard test methods, some of which are proposed in this paper, and to improve the standard stopping distance exception language and operator blind spot language in AGV standards

Watch Your Step! Terrain Traversability for Robot Control

Watch your step! Or perhaps, watch your wheels. Whatever the robot is, if it puts its feet, tracks, or wheels in the wrong place, it might get hurt; and as robots are quickly going from structured and completely known environments towards uncertain and unknown terrain, the surface assessment becomes an essential requirement. As a result, future mobile robots cannot neglect the evaluation of terrain’s structure, according to their driving capabilities. With the objective of filling this gap, the focus of this study was laid on terrain analysis methods, which can be used for robot control with particular reference to autonomous vehicles and mobile robots. Giving an overview of theory related to this topic, the investigation not only covers hardware, such as visual sensors or laser scanners, but also space descriptions, such as digital elevation models and point descriptors, introducing new aspects and characterization of terrain assessment. During the discussion, a wide number of examples and methodologies are exposed according to different tools and sensors, including the description of a recent method of terrain assessment using normal vectors analysis. Indeed, normal vectors has demonstrated great potentialities in the field of terrain irregularity assessment in both on‐road and off‐road environments

Modeling Robotic Systems with Activity Flow Graphs

Autonomous robotic systems are becoming increasingly common in our society, with research efforts towards automated goods transportation, service robots and autonomous cars. These complex systems have to solve many different problems in order to function robustly. Two especially important areas of interest are perception and high level control. Intelligent systems have to perceive their surroundings in order to facilitate autonomy. With an understanding of the environment, they then can make their own decisions based on high level control policies defined by the developers. Robotic systems differ drastically in their sensory capabilities, their computational power, and their designated tasks. When developing algorithms, however, we need to have a common modeling framework that enables us to generalize and re-use existing solutions. A modular approach, which is coherent across different platforms, also allows faster prototyping of new systems. In this dissertation we develop a modeling framework based on data flow that achieves this goal. We first extend the existing Synchronous Data Flow (SDF) model and combine it with reactive programming ideas and finite-state machines. Together, these existing frameworks enable us to model many aspects of complex robotic systems. We apply this model to a robot in a warehouse scenario to demonstrate the viability of the approach. Using three disjoint formalisms to model a robotic system has many downsides. In a first unification step we merge SDF and reactive programming into Hybrid Flow Graphs (HFGs), where we explicitly model synchronous and asynchronous data flow. We then apply the HFG model to the perception system of an autonomous transportation robot. In a last step, we eliminate the need for separate finite-state machines by introducing the concept of activity into the data flow. We therefore unify the different aspects into a single and coherent framework which we call Activity Flow Graphs (AFGs). The flow of activity enables us to model high level state directly in the data flow graph. The result is a single computation graph that can express both perception and high level control aspects of any robotic system. We then demonstrate this with multiple high level robotic system models. Finally, we make use of the uniform AFG model to provide a single graphical user interface that allows a developer to rapidly prototype complete robotic systems. Since all aspects of a robot can be implemented using the same theoretical framework, there is no need to switch between different paradigms. The user interface is designed to give immediate feedback, which speeds up prototyping, testing and evaluation, as well as debugging when working with real robots.Autonome Roboter werden zunehmend zu einem wichtigen Bestandteil unserer Gesellschaft, in Bereichen wie dem automatisierten Gütertransport, in der Servicerobotik und bei autonomen Automobilen. Diese komplexen Systeme müssen viele Problem lösen, um robust zu funktionieren. Zwei sehr wichtige Anwendungsfelder sind die Umgebungswahrnehmung und die Ablaufplanung. Intelligente Systeme müssen ihre Umgebung wahrnehmen, um autonom agieren zu können. Mit einem Verständnis der Umwelt können sie Entscheidungen treffen, welche auf abstrakten Richtlinien der Entwickler basieren. Verschiedene Roboter weichen stark in ihren sensorischen Fähigkeiten, in ihrer Rechenleistung und in ihren zu lösenden Aufgaben voneinander ab. Bei der Entwicklung von Algorithmen wird jedoch ein einheitliches Modellierungssystem benötigt, welches die Wiederverwendung von existierenden Lösungen erlaubt. Ein modulares System, welches über mehrere Plattformen hinweg genutzt werden kann, ermöglicht eine schnellere Entwicklung von neuen Systemen. In dieser Dissertation wird ein auf Datenfluss basierendes Modell entwickelt, welches diese Anforderungen erfüllt. Zuerst wird das existierende Synchronous Data Flow (SDF) Modell erweitert und mit Elementen von reaktiver Programmierung und endlichen Zustandsautomaten kombiniert. Zusammen können so viele Aspekte von Robotern modelliert werden. Das Modell wird auf einen Roboter in einem Warenhausszenario angewandt, um den Ansatz zu validieren. Drei verschiedene Formalismen zur Modellierung von Robotern zu verwenden hat viele Nachteile. In einem ersten Vereinigungsschritt werden SDF und reaktive Programmierung zu hybriden Flussgraphen (HFG) kombiniert, bei denen synchroner und asynchroner Datenfluss explizit modelliert werden. Dann wird das HFG-Modell auf die Wahrnehmungsmodule eines autonomen Transportsystems angewandt. Anschließend wird der Bedarf eines Zustandsautomaten beseitigt, indem das Konzept der Aktivität in den Datenfluss eingeführt wird. Dadurch werden alle Aspekte in einem einzigen, schlüssigen System vereinigt, welches Aktivitätsflussgraph (AFG) genannt wird. Der Aktivitätsfluss ermöglicht es, den höheren Systemzustand direkt im Datenflussgraphen zu modellieren. Als Ergebnis erhalten wir einen einzigen Berechnungsgraphen, der sowohl zur Beschreibung der Umgebungswahrnehmung als auch zur Kontrolle der höheren Abläufe benutzt werden kann. Dies wird anhand mehrerer Robotersysteme demonstriert. Eine graphische Benutzerschnittstelle wird bereitgestellt, welche von dem einheitlichen Modell Gebrauch macht, um ein schnelles Prototyping von Robotern zu ermöglichen. Da alle Aspekte mit demselben System modelliert werden, muss nicht zwischen verschiedenen Paradigmen gewechselt werden. Die Nutzerschnittstelle erleichtert Entwicklung, Test und Validierung von Algorithmen sowie das Auffinden von Fehlern bei echten Robotern

Robots learn to behave: improving human-robot collaboration in flexible manufacturing applications

L'abstract è presente nell'allegato / the abstract is in the attachmen

A new HW/SW architecture to move from AGVs towards Autonomous Mobile Robots

This paper proposes the basic concepts of a brand new HW/SW architecture, whose development is in progress through an academic/industrial collaboration, aimed at obtaining a mobile agent capable to merge in itself the standard characteristics of the Automated Guided Vehicles and some potentialities of the Autonomous Mobile Robots, with a particular care for safety issues. Its HW/SW features, together with its mechanical characteristics, make it potentially applicable both in industrial and research contexts

Safe navigation and human-robot interaction in assistant robotic applications

L'abstract è presente nell'allegato / the abstract is in the attachmen

Robots in Industry. Past,present and future of a growing collaboration with humans

Robots have been part of automation systems for a very long time, and in public perception, they are often synonymous with automation and industrial revolution perse. Fueled by Industry 4.0 and Internet of Things (IoT) concepts as well as by new software technologies, the field of robotics in industry is currently undergoing a revolution on its own. This article gives an overview of the evolution of robotics from its beginnings to recent trends like collaborative robotics, autonomous robots, and human- robot interaction. Particular attention is devoted to the deep changes of the last decades, from the traditional industrial scenario based on isolated robotic cells up to the most recent coworking and collaborative robots. The role of robotics in the Industry 4.0 framework is analyzed, and the relationships with industrial communications and software technologies are also discussed. Some future directions for robotics are envisaged, focusing on the contributions coming from new materials, sensors, actuators, and technologies. Open issues are highlighted as well as the main barriers that currently limit the deployment of industrial robots in the small and medium enterprise (SME) world

Indoor and outdoor localization for AGVs in the primary aluminum industry

The goal of this project is to analyze two types of AGV indoor and outdoor localization techniques in an aluminum smelter building with a particular operative vehicle. The indoor localization is performed with the ARTag markers system while the outdoor localization employs multiple Wi-Fi transceivers to trilaterate the position of the vehicle based on the RSSI value. Finally, raw estimated pose is fused with the IMU sensor data using the extended kalman filter to increase localization accuracy.openEmbargo tempraneo per motivi di segretezza e/o di proprietà dei risultati e informazioni di enti esterni o aziende private che hanno partecipato alla realizzazione del lavoro di ricerca relativo alla tes