7,576 research outputs found
SOTER: A Runtime Assurance Framework for Programming Safe Robotics Systems
The recent drive towards achieving greater autonomy and intelligence in
robotics has led to high levels of complexity. Autonomous robots increasingly
depend on third party off-the-shelf components and complex machine-learning
techniques. This trend makes it challenging to provide strong design-time
certification of correct operation.
To address these challenges, we present SOTER, a robotics programming
framework with two key components: (1) a programming language for implementing
and testing high-level reactive robotics software and (2) an integrated runtime
assurance (RTA) system that helps enable the use of uncertified components,
while still providing safety guarantees. SOTER provides language primitives to
declaratively construct a RTA module consisting of an advanced,
high-performance controller (uncertified), a safe, lower-performance controller
(certified), and the desired safety specification. The framework provides a
formal guarantee that a well-formed RTA module always satisfies the safety
specification, without completely sacrificing performance by using higher
performance uncertified components whenever safe. SOTER allows the complex
robotics software stack to be constructed as a composition of RTA modules,
where each uncertified component is protected using a RTA module.
To demonstrate the efficacy of our framework, we consider a real-world
case-study of building a safe drone surveillance system. Our experiments both
in simulation and on actual drones show that the SOTER-enabled RTA ensures the
safety of the system, including when untrusted third-party components have bugs
or deviate from the desired behavior
Cyber-Virtual Systems: Simulation, Validation & Visualization
We describe our ongoing work and view on simulation, validation and
visualization of cyber-physical systems in industrial automation during
development, operation and maintenance. System models may represent an existing
physical part - for example an existing robot installation - and a software
simulated part - for example a possible future extension. We call such systems
cyber-virtual systems.
In this paper, we present the existing VITELab infrastructure for
visualization tasks in industrial automation. The new methodology for
simulation and validation motivated in this paper integrates this
infrastructure. We are targeting scenarios, where industrial sites which may be
in remote locations are modeled and visualized from different sites anywhere in
the world.
Complementing the visualization work, here, we are also concentrating on
software modeling challenges related to cyber-virtual systems and simulation,
testing, validation and verification techniques for them. Software models of
industrial sites require behavioural models of the components of the industrial
sites such as models for tools, robots, workpieces and other machinery as well
as communication and sensor facilities. Furthermore, collaboration between
sites is an important goal of our work.Comment: Preprint, 9th International Conference on Evaluation of Novel
Approaches to Software Engineering (ENASE 2014
Qduino: a cyber-physical programming platform for multicore Systems-on-Chip
Emerging multicore Systems-on-Chip are enabling new cyber-physical applications such as autonomous drones, driverless cars and smart manufacturing using web-connected 3D printers. Common to those applications is a communicating task pipeline, to acquire and
process sensor data and produce outputs that control actuators. As a result, these applications usually have timing requirements for both individual tasks and task pipelines formed for sensor data processing and actuation. Current cyber-physical programming platforms, such as Arduino and embedded Linux with the POSIX interface do not allow application developers to specify those timing requirements. Moreover, none of them provide the programming interface to schedule tasks and map them to processor cores, while managing I/O in a predictable manner, on multicore hardware platforms. Hence, this thesis presents the Qduino programming platform. Qduino adopts the simplicity of the Arduino API, with additional support for real-time multithreaded sketches on multicore architectures. Qduino allows application developers to specify timing properties of individual tasks as well as task pipelines at the design stage. To this end, we propose a mathematical framework to derive each task’s budget and period from the specified end-to-end timing requirements.
The second part of the thesis is motivated by the observation that at the center of these pipelines are tasks that typically require complex software support, such as sensor data fusion or image processing algorithms. These features are usually developed by many man-year engineering efforts and thus commonly seen on General-Purpose Operating Systems (GPOS). Therefore, in order to support modern, intelligent cyber-physical applications, we enhance the Qduino platform’s extensibility by taking advantage of the Quest-V virtualized partitioning kernel. The platform’s usability is demonstrated by building a novel web-connected 3D printer and a prototypical autonomous drone framework in Qduino
Adaptive Process Management in Cyber-Physical Domains
The increasing application of process-oriented approaches in new challenging cyber-physical domains beyond business computing (e.g., personalized healthcare, emergency management, factories of the future, home automation, etc.) has led to reconsider the level of flexibility and support required to manage complex processes in such domains. A cyber-physical domain is characterized by the presence of a cyber-physical system coordinating heterogeneous ICT components (PCs, smartphones, sensors, actuators) and involving real world entities (humans, machines, agents, robots, etc.) that perform complex tasks in the “physical” real world to achieve a common goal. The physical world, however, is not entirely predictable, and processes enacted in cyber-physical domains must be robust to unexpected conditions and adaptable to unanticipated exceptions. This demands a more flexible approach in process design and enactment, recognizing that in real-world environments it is not adequate to assume that all possible recovery activities can be predefined for dealing with the exceptions that can ensue. In this chapter, we tackle the above issue and we propose a general approach, a concrete framework and a process management system implementation, called SmartPM, for automatically adapting processes enacted in cyber-physical domains in case of unanticipated exceptions and exogenous events. The adaptation mechanism provided by SmartPM is based on declarative task specifications, execution monitoring for detecting failures and context changes at run-time, and automated planning techniques to self-repair the running process, without requiring to predefine any specific adaptation policy or exception handler at design-time
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