Software tools for the cognitive development of autonomous robots

Robotic systems are evolving towards higher degrees of autonomy. This paper reviews the cognitive tools available nowadays for the fulfilment of abstract or long-term goals as well as for learning and modifying their behaviour.Peer ReviewedPostprint (author's final draft

Eine Referenzarchitektur für die assistierte und automatisierte Fahrzeugführung mit Fahrereinbindung

Gegenstand der Arbeit ist die Entwicklung einer funktionalen Systemarchitektur, die den Anforderungen des assistierten, teilautomatisierten bis hin zum vollautomatisierten Fahrens gerecht werden soll. Dabei steht insbesondere die Architektur als wissenschaftliche Disziplin im Vordergrund, in der Entscheidungsalternativen erarbeitet und durch Abwägung der sich daraus ergebenden Konsequenzen bewertet und dokumentiert werden. Im ersten Schritt erfolgt eine Anforderungsanalyse, in der die funktionalen Systemanforderungen in Form notwendiger Fahrmanöver hergeleitet sowie relevante nichtfunktionale Anforderungen (insbes. Test- und Erweiterbarkeit) an die Architektur identifiziert werden. Darauf aufbauend erfolgt die Entwicklung der Referenzarchitektur auf Basis hybrider Robotik-Basisarchitekturen, beginnend mit einer Festlegung des 3-Ebenen Fahrzeugführungsmodelles nach Donges als zugrunde liegendes hierarchisches Abstraktionsmodell. Von besonderer Bedeutung dabei ist das Zusammenspiel zwischen deliberativen Systemelementen zur Zielerreichung einerseits und reaktiven Systemelementen zur schnellen Reaktion auf sich ändernde Situationsparameter andererseits. Als Ergebnis liegt ein hierarchisches Mehrebenensystem mit vier Systemebenen vor. Neben der Festlegung der Kontrollhierarchie wird zusätzlich der Informationsbedarf der Planungsmodule in Richtung des Umfeldmodells skizziert sowie die notwendigen Mensch-Maschine-Schnittstellen zur Fahrereinbindung

Gesture-Based Robot Path Shaping

For many individuals, aging is frequently associated with diminished mobility and dexterity. Such decreases may be accompanied by a loss of independence, increased burden to caregivers, or institutionalization. It is foreseen that the ability to retain independence and quality of life as one ages will increasingly depend on environmental sensing and robotics which facilitate aging in place. The development of ubiquitous sensing strategies in the home underpins the promise of adaptive services, assistive robotics, and architectural design which would support a person\u27s ability to live independently as they age. Instrumentation (sensors and processing) which is capable of recognizing the actions and behavioral patterns of an individual is key to the effective component design in these areas. Recognition of user activity and the inference of user intention may be used to inform the action plans of support systems and service robotics within the environment. Automated activity recognition involves detection of events in a sensor data stream, conversion to a compact format, and classification as one of a known set of actions. Once classified, an action may be used to elicit a specific response from those systems designed to provide support to the user. It is this response that is the ultimate use of recognized activity. Hence, the activity may be considered as a command to the system. Extending this concept, a set of distinct activities in the form of hand and arm gestures may form the basis of a command interface for human-robot interaction. A gesture-based interface of this type promises an intuitive method for accessing computing and other assistive resources so as to promote rapid adoption by elderly, impaired, or otherwise unskilled users. This thesis includes a thorough survey of relevant work in the area of machine learning for activity and gesture recognition. Previous approaches are compared for their relative benefits and limitations. A novel approach is presented which utilizes user-generated feedback to rate the desirability of a robotic response to gesture. Poorly rated responses are altered so as to elicit improved ratings on subsequent observations. In this way, responses are honed toward increasing effectiveness. A clustering method based on the Growing Neural Gas (GNG) algorithm is used to create a topological map of reference nodes representing input gesture types. It is shown that learning of desired responses to gesture may be accelerated by exploiting well-rewarded actions associated with reference nodes in a local neighborhood of the growing neural gas topology. Significant variation in the user\u27s performance of gestures is interpreted as a new gesture for which the system must learn a desired response. A method for allowing the system to learn new gestures while retaining past training is also proposed and shown to be effective

The Almost People: A framework proposal for the balancing of legal interests in the age of social robots.

Robots, which were seen as gimmicks in science fiction stories until not so long ago, have already crossed into reality. Thanks to the ever-growing autonomy of robots and ever-expanding variety of roles assigned to them, they are becoming more integrated into the ordinary course of everyday life. With the advent of social robots that can engage human beings on personal levels, for the first time, non-human entities are emerging as social interaction partners. In that regard, from the legal perspective, it is no longer possible to treat them as mere tools. The autonomy of robots is expected to have significant impacts on various interests recognised by the legal principles that underlie existing legal instruments. However, almost none of the existing legal instruments were developed in consideration of the implications of robots' emerging roles as independent social actors. On explaining the inadequacy of existing legal instruments, I outline the prospect of a paradigm shift in the law's approach to human-robot social interactions. A comparative analysis of German, Italian, and Irish legal systems -selected to represent the EU's diverse legal families- demonstrates that robots' autonomous behaviours and emerging roles as social interaction partners are likely to undermine the legal principles expressed most notably in the domains of private law (contract law and tort law) and criminal law. The conceptual deconstruction of existing legal instruments offered by these domains reveals that legal systems overlook the characteristics of social robots that set them apart from other artefacts, namely, their relative autonomy and social agency. These distinctive characteristics allow robots to perform unpredictable behaviours and to prompt human beings they interact with to anthropomorphise them. Overlooking these characteristics diminishes the adequacy of existing legal instruments Ultimately, I conclude that the shortcomings of contemporary legal systems can be overcome by creating a new, unified legal framework that would enable the law to respond to the legal implications of robot autonomy and the phenomenon of robot anthropomorphism

Multi-Agent Systems

This Special Issue ""Multi-Agent Systems"" gathers original research articles reporting results on the steadily growing area of agent-oriented computing and multi-agent systems technologies. After more than 20 years of academic research on multi-agent systems (MASs), in fact, agent-oriented models and technologies have been promoted as the most suitable candidates for the design and development of distributed and intelligent applications in complex and dynamic environments. With respect to both their quality and range, the papers in this Special Issue already represent a meaningful sample of the most recent advancements in the field of agent-oriented models and technologies. In particular, the 17 contributions cover agent-based modeling and simulation, situated multi-agent systems, socio-technical multi-agent systems, and semantic technologies applied to multi-agent systems. In fact, it is surprising to witness how such a limited portion of MAS research already highlights the most relevant usage of agent-based models and technologies, as well as their most appreciated characteristics. We are thus confident that the readers of Applied Sciences will be able to appreciate the growing role that MASs will play in the design and development of the next generation of complex intelligent systems. This Special Issue has been converted into a yearly series, for which a new call for papers is already available at the Applied Sciences journal’s website: https://www.mdpi.com/journal/applsci/special_issues/Multi-Agent_Systems_2019

Modeling of motion primitive architectures using domain-specific languages

Nordmann A. Modeling of motion primitive architectures using domain-specific languages. Bielefeld: Universität Bielefeld; 2016