Programmable logic controllers (PLCs) are an established platform, widely used throughout industrial automation but poorly understood among researchers. This article gives an overview of the state of the practice, explaining why this settled technology persists throughout industry and presenting a critical analysis of the strengths and weaknesses of the dominant programming styles for today's PLC-based automation systems. We describe the software execution patterns that are standardized loosely in IEC 61131-3. We identify opportunities for improvements that would enable increasingly complex industrial automation applications while strengthening safety and reliability. Specifically, we propose deterministic, distributed programming models that embrace explicit timing, event-triggered computation, and improved security.

We discuss a novel approach for constructing deterministic reactive systems that evolves around a temporal model which incorporates a multiplicity of timelines. This model is central to LINGUA FRANCA (LF), a polyglot coordination language and compiler toolchain we are developing for the definition and composition of concurrent components called Reactors, which are objects that react to and emit discrete events. What sets LF apart from other languages that treat time as a first-class citizen is that it confronts the issue that in any reactive system there are at least two distinct timelines involved; a logical one and a physical one-and possibly multiple of each kind. LF provides a mechanism for relating events across timelines, and guarantees deterministic program behavior under quantifiable assumptions.

Accurate localization from Cyber-Physical Systems (CPS) is a critical enabling technology for context-aware applications and control. As localization plays an increasingly safety-critical role, location systems must be able to identify and eliminate faulty measurements to prevent dangerously inaccurate localization. In this article, we consider the range-based localization problem and propose a method to detect coordinated adversarial corruption on anchor positions and distance measurements. Our algorithm, G ordian , rapidly finds attacks by identifying geometric inconsistencies at the graph level without requiring assumptions about hardware, ranging mechanisms, or cryptographic protocols. We give necessary conditions for which attack detection is guaranteed to be successful in the noiseless case, and we use that intuition to extend G ordian to the noisy case where fewer guarantees are possible. In simulations generated from real-world sensor noise, we empirically show that G ordian ’s trilateration counterexample generation procedure enables rapid attack detection even for combinatorially difficult problems.

Connected cars have the potential to transform a vehicle from a transportation platform to a platform for integrating humans with a city. To that end we introduce semantic accessors (actor based local proxies for remote services) as a novel, and powerful discovery mechanism for connected vehicles that bridges the domains of Internet of Things (IoT) composition frameworks and the semantic web of things. The primary components of this approach include a local semantic repository used for maintaining the vehicle's perspective of its real-world context, accessors for querying and dynamically updating the repository to match evolving vehicular context information, accessors for services (such as parking) linked to a service ontology, and a swarmlet controller responsible for managing the above in accordance with user input. We demonstrate this semantic accessor architecture with a prototype Dashboard display that downloads accessors for new services as they become available and dynamically renders their self-described user interface components.

In this paper, we describe a component-based software architecture for the Internet of Things in which proxies for Things and services that we call “accessors” interact with one another under a concurrent, time-stamped, discrete-event (DE) semantics. These proxies are analogous to web pages, which proxy a cloud-based service such as a bank, but instead of being designed to interface those services with humans, accessors are designed to interface services and Things with other services and Things. A deterministic DE semantics is combined with a widely used pattern for handling network interactions that we call asynchronous atomic callbacks (AACs). AAC enables many concurrent pending requests to be active at once without blocking and without the treacherous concurrency pitfalls of threads. In effect, our architecture combines AAC with actors where the actor model has been endowed with a temporal semantics. We show how this architecture can leverage the previously reported secure swarm toolkit (SST) to achieve stateof- the-art authentication, authorization, and encryption of interactions across networks.

During robotic teleoperation, the dynamics of the master manipulators and the control of remote-side instruments impose challenges on the motor system of the human operator, and may impact performance and learning. In teleoperated robot-assisted minimally invasive surgery, there is a clear correlation between patient outcomes and the surgeon's case experience. However, the effect of the teleoperator on human motor skills and the relationship between these motor skills and patient outcomes are unknown. We used the da Vinci Research Kit, a custom research version of the da Vinci Surgical System, to compare teleoperated and open needle-driving movements of experienced da Vinci surgeons and novices. The experimental protocol consisted of structured but unconstrained needle driving trials repeated 80 times to allow for computational modeling of movement coordination and learning. Kinematic analysis showed that teleoperation increases trial time but reduces path length, that the trial times and path lengths of experienced surgeons are smaller than those of novices. In addition, there are significant differences in learning between experienced surgeons and novice users. Modeling of the movements and learning processes of experienced and novice surgeons may be used in the design of novel controllers that will expand robotic surgery capabilities and improve robot-assisted surgical skill acquisition.

We propose a model for Semantic Localization, i.e. establishing positional relations on meaningful objects, to enable the principled integration of heterogeneous localization clues -- such as those derived from ubiquitous sensors in the Internet of Things. Our approach is two-pronged: we consider relation-structured Phenomenal Maps alongside spatially-organized Physical Maps. Phenomenal Maps may be used to answer semantic queries about the relative position of objects without necessarily resorting to physical coordinates. Physical Maps are not restricted to purely Euclidian spaces, to the contrary we identify useful applications for topological, and metrical maps among others. We give the framework for a structured mechanism through which localization information in all these representations may be reconciled.

Recent imprecise hardware (IHW) design methodologies present opportunities for achieving gains in nonfunctional efficiency design metrics by allowing errors in computation within error tolerant application domains. This work presents a novel imprecise Error Tolerant Balancing Adder (ETBA) design - an augmentation of the ETAIIM IHW adder that reduces errors by introducing a balance block that detects and corrects carry chain inconsistencies in the ETAIIM but operates off the critical path. Furthermore, this work identifies a common class of killer inputs with high error rates for IHW adders, and demonstrates the ETBA's resilience to these errors. A JPEG decompression case study reveals a 24% reduction in ETBA addition energy-delay product compared to a Kogge-Stone adder with only a 0.2% reduction in SSIM image quality.