Virtual Neurorobotics (VNR) to Accelerate Development of Plausible Neuromorphic Brain Architectures

Traditional research in artificial intelligence and machine learning has viewed the brain as a specially adapted information-processing system. More recently the field of social robotics has been advanced to capture the important dynamics of human cognition and interaction. An overarching societal goal of this research is to incorporate the resultant knowledge about intelligence into technology for prosthetic, assistive, security, and decision support applications. However, despite many decades of investment in learning and classification systems, this paradigm has yet to yield truly “intelligent” systems. For this reason, many investigators are now attempting to incorporate more realistic neuromorphic properties into machine learning systems, encouraged by over two decades of neuroscience research that has provided parameters that characterize the brain's interdependent genomic, proteomic, metabolomic, anatomic, and electrophysiological networks. Given the complexity of neural systems, developing tenable models to capture the essence of natural intelligence for real-time application requires that we discriminate features underlying information processing and intrinsic motivation from those reflecting biological constraints (such as maintaining structural integrity and transporting metabolic products). We propose herein a conceptual framework and an iterative method of virtual neurorobotics (VNR) intended to rapidly forward-engineer and test progressively more complex putative neuromorphic brain prototypes for their ability to support intrinsically intelligent, intentional interaction with humans. The VNR system is based on the viewpoint that a truly intelligent system must be driven by emotion rather than programmed tasking, incorporating intrinsic motivation and intentionality. We report pilot results of a closed-loop, real-time interactive VNR system with a spiking neural brain, and provide a video demonstration as online supplemental material

Technologies for safe and resilient earthmoving operations: A systematic literature review

Resilience engineering relates to the ability of a system to anticipate, prepare, and respond to predicted and unpredicted disruptions. It necessitates the use of monitoring and object detection technologies to ensure system safety in excavation systems. Given the increased investment and speed of improvement in technologies, it is necessary to review the types of technology available and how they contribute to excavation system safety. A systematic literature review was conducted which identified and classified the existing monitoring and object detection technologies, and introduced essential enablers for reliable and effective monitoring and object detection systems including: 1) the application of multisensory and data fusion approaches, and 2) system-level application of technologies. This study also identified the developed functionalities for accident anticipation, prevention and response to safety hazards during excavation, as well as those that facilitate learning in the system. The existing research gaps and future direction of research have been discussed

Autonomiset työkoneet ja autonomian vaikutus koneturvallisuuteen

Autonomous machines and vehicles are an increasing part of everyday life and industrial operations. These machines and vehicles have enjoyed rapid technological advancements in recent years, which has led to increasingly sophisticated functions and functionalities. The advancements in autonomous technologies have, however, given rise to questions and concerns relating to the safety of these machines and vehicles, and on how an adequate level of safety can be ensured when no dedicated operator or driver is present. This thesis looks at the main areas that affect the overall safety of autonomous industrial machines and civilian road vehicles, and presents the most prominent challenges faced in ensuring the safety of autonomous applications. The goal of the thesis is to give the reader an overview of the safety-related aspects of autonomy and to show what has to be considered when ensuring an adequate level of safety for autonomous machines or vehicles. This is achieved by an extensive literature review on autonomous applications in both industrial and automotive fields, and on the safety-related aspects of autonomy. Additionally, mining is used in the thesis as an example of autonomous machines in practice and on the challenges autonomy can face in industrial operations. Based on the research carried out, it can be said that the overall safety of machine autonomy is currently hindered by two main aspects: the lack of applicable standards, legislation and guidelines regarding the autonomy of machines and vehicles, and the paradox that arises from balancing the desired level of autonomy with the needed level of safety. This has led to a situation where, in theory, highly complex and sophisticated autonomous machines are possible from a technical standpoint, but they lack a common and thorough method for ensuring an adequate level of safety

Safe and effective navigation of autonomous robots in hazardous environments.

The development of autonomous mobile machines to perform useful tasks in real work environments is currently being impeded by concerns over effectiveness, commercial viability and, above all, safety. This paper introduces a case study of a robotic excavator to explore a series of issues around system development, navigation in unstructured environments, autonomous decision making and changing the behaviour of autonomous machines to suit the prevailing demands of users. The adoption of the Real-Time Control Systems (RCS) architecture (Albus, 1991) is proposed as a universal framework for the development of intelligent systems. In addition it is explained how the use of Partially Observable Markov Decision Processes (POMDP) (Kaelbling et al., 1998) can form the basis of decision making in the face of uncertainty and how the technique can be effectively incorporated into the RCS architecture. Particular emphasis is placed on ensuring that the resulting behaviour is both task effective and adequately safe, and it is recognised that these two objectives may be in opposition and that the desired relative balance between them may change. The concept of an autonomous system having “values” is introduced through the use of utility theory. Limited simulation results of experiments are reported which demonstrate that these techniques can create intelligent systems capable of modifying their behaviour to exhibit either ‘safety conscious’ or ‘task achieving’ personalities

Análise cinemática via quatérnios duais aplicada a um sistema veículo-manipulador subaquático

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia de Automação e Sistemas, Florianópolis, 2011Este trabalho propõe metodologias para a análise cinemática de sistemas veículo-manipulador subaquáticos (UVMS) através de quatérnios duais com o intuito de impor menor variação de torque nas juntas durante o seguimento de trajetória. Em adição a isso, evita-se a ocorrência de singularidades cinemáticas e obtém-se menor custo computacional. A abordagem é apresentada inicialmente como uma alternativa à representação tradicional dos movimentos aplicada na cinemática direta de mecanismos através da convenção de Denavit-Hartenberg e do método dos helicoides sucessivos. O benefício dessa representação está no menor custo computacional, mas principalmente, no desacoplamento dos ângulos de orientação de forma a evitar as singularidades cinemáticas. Os quatérnios duais também são aplicados na cinemática inversa em uma metodologia interativa através do método de Davies como uma modalidade de realimentação livre de singularidades. Por fim, a principal contribuição deste trabalho está na proposta da aplicação dos quatérnios duais na cinemática inversa diferencial em por uma metodologia analítica, através da apresentação do Jacobiano dual-quaterniônico. Essas abordagens são aplicadas a um sistema subaquático, onde o amortecimento imposto pela imersão no fluido dissipa grandes variações de torque e agrega erros no seguimento da trajetória.This work proposes a methodology for kinematic analysis of underwater vehicle-manipulator systems (UVMS) using dual-quaternions. The objective is to provide a less joint torque variation to trajectory tracking, avoidance of kinematic singularities occurrence and a lower computational cost. The approach is initially presented as an alternative representation of movements applied to direct kinematics through the Denavit- Hartenberg convention and the successive screws method. The benefit of this representation is a lower computational cost, but mainly, the decoupling of orientation angles in order to avoid kinematic singularities. The dual quaternions also are applied in the inverse kinematics in an interactive approach through Davies method as a feedback without singularities. Finally, the main contribution of this work is the proposal of dual quaternions application in an analytical approach of differential inverse kinematics through of the dual-quaternionic Jacobian. These approaches are applied to an underwater system, where the damping imposed by fluid immersion dissipates large torque variations adding errors in trajectory tracking

Safety of Autonomous Cognitive-oriented Robots

Service robots shall very soon autonomously provide services in all spheres of life by executing demanding and complex tasks in dynamic, complex environments and by collaborating with human users. In order to push forward the understanding of the safety problem a novel classification of robot hazards is provided. The so-called object interaction hazards are derived which arise when environment objects interact with objects that are manipulated by a robot. Taking into account the current state-of-the-art, it can be stated that this denotes a novel problem area. However, it is already proposed the so-called dynamic risk assessment approach, which shall enable the robot to perceive the risk of current and upcoming situations. In order to realize such a risk-aware planning system for the first time, dynamic risk assessment is integrated within a cognitive architecture serving cognitive functions like anticipation, planning and learning. In this connection, action spaces (sets of possible upcoming situations) are dynamically anticipated assessed with regard to comprised risks. Though, (initial) knowledge about hazards is required in order to realize this. Therefore, a novel procedural model is developed for systematically generating a safety knowledge base. However, it can be assumed that the safety knowledge potentially lacks completeness. The application of AI-based approaches constitutes a noteworthy opportunity. For this reason, light is shed on strategically influential learning methods in safety-critical contexts. Finally, this work describes the generation, integration, utilization, and maintenance of a system-internal safety knowledge base for dynamic risk assessment. It denotes an overall concept toward solving the advanced safety problem and confirms in principle the realization of a safe behavior of autonomous and intelligent systems.Sicherheit autonomer kognitivorientierter Roboter Autonome mobile Serviceroboter sollen zukünftig selbstständig Dienstleistungen in allen Lebensbereichen erbringen, auch in direkter Nähe zum Menschen. Um das Verständnis für Sicherheit in der Robotik zu erwei-tern, wird zunächst eine neue Klassifizierung der möglichen Gefahren vorgenommen. Hiervon wird die Klasse der Objektinteraktionsgefahren abgeleitet. Diese Gefahren entstehen, wenn Objekte der Umgebung mit denen interagieren, die der Roboter greift und transportiert. In Anbetracht des aktuellen Standes der Sicherheits-technik in der Robotik wird klar, dass sich hier ein neues Problemfeld auftut. Grundsätzlich wurde bereits ein dynamischer Risikountersuchungsansatz vorgeschlagen, welcher den Roboter selbst befähigen soll, Situatio-nen hinsichtlich möglicher Gefahren zu untersuchen. Um dadurch eine risikobewusste Handlungsplanung erstmals zu realisieren, wird dieser in eine kognitive Architektur integriert, um kognitive Funktionen, wie Anti-zipation, Planen und Lernen zu nutzen. Hierbei werden mögliche Handlungsräume dynamisch antizipiert und mittels dynamischer Risikoanalyse auf mögliche Gefahren untersucht. Um (Objektinteraktions-) Gefahren mit Hilfe der dynamischer Risikountersuchung bestimmen zu können, bedarf es eines (initialen) Wissens über mögliche Gefahren. Aus diesem Grund wird ein Vorgehensmodell zur systematischen Erzeugung einer solchen Sicherheitswissensbasis entwickelt. Dieses Sicherheitswissen ist jedoch potentiell unvollständig. Daher stellt die Erweiterung und Verfeinerung desselben eine Notwendigkeit dar. Hierbei können die Ansätze aus dem Bereich der künstlichen Intelligenz als nützliche Möglichkeit wahrgenommen werden. Daher werden strate-gisch wichtige Lernmethoden hinsichtlich der Anwendung in einem sicherheitskritischen Kontext untersucht. Die vorliegende Arbeit beschreibt die Erzeugung, die Integration, die Verwendung und die Aufrechterhaltung einer systeminternen Sicherheitswissensbasis zum Zwecke der dynamischen Risikountersuchung. Sie stellt hierbei ein Gesamtkonzept dar, dass zur Lösung des erweiterten Sicherheitsproblems beiträgt und somit die prinzipielle Realisierung des sicheren Betriebs von autonomen und intelligenten bestätigt