With an increasing degree of automation, automated vehicle systems become more complex in terms of functional components as well as interconnected hardware and software components. Thus, holistic systems engineering becomes a severe challenge. Emergent properties like system safety are not solely arguable in singular viewpoints such as structural representations of software or electrical wiring (e.g. fault tolerant). This states the need to get several viewpoints on a system and describe correspondences between these views in order to enable traceability of emergent system properties. Today, the most abstract view found in architecture frameworks is a logical description of system functions which structures the system in terms of information flow and functional components. In this article we extend established system viewpoints towards a capability-based assessment of an automated vehicle and conduct an exemplary safety analysis to derive behavioral safety requirements. These requirements can afterwards be attributed to different viewpoints in an architecture frameworks and thus be integrated into a development process for automated vehicles.
A singular perspective on functionality is not sufficient. Especially when it comes to developing an autonomous vehicle, a deeper review of constraints and requirements (e.g. regarding performance) is necessary for structuring an overall system. Coste-Mani ere and Simmons @cite_17 states that architectures are the foundation of designing, implementing and validating robotic systems. Depending on the needs of the different applications provided in a system, different architectures are necessary.
@cite_17
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Architectures form the backbone of complete robotic systems. The right choice of architecture can go a long way in facilitating the specification, implementation and validation of robotic systems. Conversely, of course, the wrong choice can make one's life miserable. We present some of the needs of robotic systems, describe some general classes of robot architectures, and discuss how different architectural styles can help in addressing those needs. The paper, like the field itself, is somewhat preliminary, yet it is hoped that it will provide guidance for those who use, or develop, robot architectures. We describe an autonomous robotic software subsystem for managing mission execution and discrete traffic interaction in the 2007 DARPA Urban Challenge. Its role is reviewed in the context of the software system that controls ldquoBossrdquo, Tartan Racingpsilas winning entry in the competition. Design criteria are presented, followed by the application of software design principles to derive an architecture well suited to the rigors of developing complex robotic systems. Combined with a discussion of robust behavioral algorithms, the designpsilas effectiveness is highlighted in its ability to manage complex autonomous driving behaviors while remaining adaptable to the systempsilas evolving capabilities. Robotic systems are complex and critical: they are inherently hybrid, combining both hardware and software; they typically exhibit both cyber-physical attributes and autonomous capabilities; and are required to be at least safe and often ethical. While for many engineered systems testing, either through real deployment or via simulation, is deemed sufficient the uniquely challenging elements of robotic systems, together with the crucial dependence on sophisticated software control and decision-making, requires a stronger form of verification. The increasing deployment of robotic systems in safety-critical scenarios exacerbates this still further and leads us towards the use of formal methods to ensure the correctness of, and provide sufficient evidence for the certification of, robotic systems. There have been many approaches that have used some variety of formal specification or formal verification in autonomous robotics, but there is no resource that collates this activity in to one place. This paper systematically surveys the state-of-the art in specification formalisms and tools for verifying robotic systems. Specifically, it describes the challenges arising from autonomy and software architectures, avoiding low-level hardware control and is subsequently identifies approaches for the specification and verification of robotic systems, while avoiding more general approaches. For robotic systems to realise lifelong autonomy they must be able to navigate accurately in changing environments. In this thesis we describe, implement and validate a new approach to the problem of long-term navigation. To begin, we present our stereo visual odometry system which provides highly accurate pose estimation. Our approach combines several techniques found in existing implementations and a recently published image descriptor that simplifies the solution architecture. The performance and versatility of our system is demonstrated through testing on multiple datasets. Equipped with our visual odometry system, we describe a new approach to the problem of lifelong navigation. We learn a model whose complexity varies naturally in accordance with the variation of scene appearance. As the robot repeatedly traverses its workspace, it accumulates distinct visual experiences that, in concert, implicitly represent the scene variation - each experience captures a visual mode. When operating in a previously visited area, we continually try to localise in these previous experiences while simultaneously running the visual odometry. Failure to localise in a sufficient number of prior experiences indicates an insufficient model of the workspace and instigates the laying down of the live image sequence as a new distinct experience. In this way, over time we can capture the typical temporally varying appearance of an environment and the number of experiences required tends to a constant. Although we focus on vision as a primary sensor, the ideas we present here are equally applicable to other sensor modalities. We demonstrate our approach working on a road vehicle operating over a three month period at different times of day, in different weather and lighting conditions.