Code Generator Composition for Model-Driven Engineering of Robotics Component & Connector Systems

Engineering software for robotics applications requires multidomain and application-specific solutions. Model-driven engineering and modeling language integration provide means for developing specialized, yet reusable models of robotics software architectures. Code generators transform these platform independent models into executable code specific to robotic platforms. Generative software engineering for multidomain applications requires not only the integration of modeling languages but also the integration of validation mechanisms and code generators. In this paper we sketch a conceptual model for code generator composition and show an instantiation of this model in the MontiArc- Automaton framework. MontiArcAutomaton allows modeling software architectures as component and connector models with different component behavior modeling languages. Effective means for code generator integration are a necessity for the post hoc integration of applicationspecific languages in model-based robotics software engineering.Comment: 12 pages, 4 figures, In: Proceedings of the 1st International Workshop on Model-Driven Robot Software Engineering (MORSE 2014), York, Great Britain, Volume 1319 of CEUR Workshop Proceedings, 201

Master of Science

thesisThis thesis details the development of the Algorithmic Robotics Laboratory, its experimental software environment, and a case study featuring a novel hardware validation of optimal reciprocal collision avoidance. We constructed a robotics laboratory in both software and hardware in which to perform our experiments. This lab features a netted flying volume with motion capture and two custom quadrotors. Also, two experimental software architectures are developed for actuating both ground and aerial robots within a Linux Robot Operating System environment. The first of the frameworks is based upon a single finite state machine program which managed each aspect of the experiment. Concerns about the complexity and reconfigurability of the finite state machine prompted the development of a second framework. This final framework is a multimodal structure featuring programs which focus on these specific functions: State Estimation, Robot Drivers, Experimental Controllers, Inputs, Human Robot Interaction, and a program tailored to the specifics of the algorithm tested in the experiment. These modular frameworks were used to fulfill the mission of the Algorithmic Robotics Lab, in that they were developed to validate robotics algorithms in experiments that were previously only shown in simulation. A case study into collision avoidance was used to mark the foundation of the laboratory through the proving of an optimal reciprocal collision avoidance algorithm for the first time in hardware. In the case study, two human-controlled quadrotors were maliciously flown in colliding trajectories. Optimal reciprocal collision avoidance was demonstrated for the first time on completely independent agents with local sensing. The algorithm was shown to be robust to violations of its inherent assumptions about the dynamics of agents and the ability for those agents to sense imminent collisions. These experiments, in addition to the mathematical foundation of exponential convergence, submits th a t optimal reciprocal collision avoidance is a viable method for holonomic robots in both 2-D and 3-D with noisy sensing. A basis for the idea of reciprocal dance, a motion often seen in human collision avoidance, is also suggested in demonstration to be a product of uncertainty about the state of incoming agents. In the more than one hundred tests conducted in multiple environments, no midair collisions were ever produced

Data-driven fault detection for component based robotic systems

Golombek R. Data-driven fault detection for component based robotic systems. Bielefeld: Universität Bielefeld; 2014.Advancements in the field of robotics enable the creation of systems with cognitive abilities which are capable of close interaction with humans in real world scenarios. These systems may take over jobs previously executed by humans like house cleaning and cooking or they can be supportive and act as a helper for elderly people. One consequence of this progress is the increased need for dependable and fault tolerant behavior of today’s robotic systems because they share the same spaces with humans and operate in close proximity to them. Unreliable and faulty behavior may frustrate users or even endanger them resulting in poor acceptance of robotic systems. The contribution of this thesis is a fault detection approach called AuCom. Fault detection is a basis element for fault tolerant system behavior which is the ability of a system to autonomously cope with occurring faults while it is engaged in interaction. The approach is designed to tackle the specific needs of cognitive robotic systems which feature a component based hardware and software structure and are characterized by frequent changes due to research and development efforts as well as uncertain and variant behavior resulting from the interaction in real world environments. The solution presented in this thesis belongs to the class of data-driven fault detection approaches. This class of approaches assumes that fault relevant information can be directly derived from data gathered in the robotic system. The data exploited in this work for fault detection is the communication between the system’s components. This communication is represented with features which are common to all elements of the communication (i.e., they are generic). Furthermore, the approach assumes that the current element of the communication can be estimated from the history of the system’s communication and that a deviation from the expected estimate indicates a fault. This assumption is encoded in the model in terms of a novel representation of the communication as a time-series of temporal dynamic features. A concrete integration of the approach into a real system is exemplified on our robotic platform BIRON. In addition, exemplary integration solutions for robotic frameworks currently prominent in literature are discussed in this thesis. The actual capability of the approach to report faults is evaluated for several artificial systems in simulation and on BIRON in an off-line and on-line manner. The performance is compared to a histogram-based baseline approach

Dimensional Analysis of Robot Software without Developer Annotations

Robot software risks the hazard of dimensional inconsistencies. These inconsistencies occur when a program incorrectly manipulates values representing real-world quantities. Incorrect manipulation has real-world consequences that range in severity from benign to catastrophic. Previous approaches detect dimensional inconsistencies in programs but require extra developer effort and technical complications. The extra effort involves developers creating type annotations for every variable representing a real-world quantity that has physical units, and the technical complications include toolchain burdens like specialized compilers or type libraries. To overcome the limitations of previous approaches, this thesis presents novel methods to detect dimensional inconsistencies without developer annotations. We start by empirically assessing the difficulty developers have in making type annotations. In a human study of 83 subjects, we find that developers are only 51% accurate and require more than 2 minutes per annotation. We further find that type suggestions have a significant impact on annotation accuracy. We find that when showing developers annotation suggestions, three suggestions are better than a single suggestion because they are as helpful when correct and less harmful when incorrect. Since developers struggle to make type annotations accurately, we present a novel method to infer physical unit types without developer annotations. This is novel because it is the first method to detect dimensional inconsistencies in ROS C++ without developer annotations, and this is important because robot software and ROS are increasingly used in real-world applications. Our method leverages a property of robotic middleware architecture that reuses standardized data structures, and we implement our method in an open-source tool, Phriky. We evaluate our method empirically on a corpus of 5.9 M lines of code and find that it detects real inconsistencies with an 87% TP rate. However, our method only assigns physical unit types to 25% of variables, leaving much of the annotation space unaddressed. To overcome these limitations, we extend our method to utilize uncertain evidence in identifiers using probabilistic reasoning. We implement our new probabilistic method in a tool Phys and find that it assigns units to 75% of variables while retaining a TP rate of 82%. We present the first open dataset of dimensional inconsistencies in open-source robotics code, to our knowledge. Lastly, we identify extensions to our work and next steps for software tool developers to build more powerful robot software development tools. Advisers: Sebastian Elbaum and Carrick Detweile

Turnkey tyranny? Struggles for a new digital order

Networking and digital communication pervade every area of life. As a consequence, norm formation on the Net has become a hotly disputed process. The chapter tracks the evolution of order in Internet politics and correlates this with the emergence of dissidence and its various manifestations. It is argued that dissidence has found a particularly conducive setting for its operations and that, thanks to the open starting position and an astute use of the expanding protest repertoire, it has managed to generate considerable public interest and high legitimacy. To what extent politicisation and dissident practice will succeed, nevertheless, remains to be seen since public approval in the field of Internet politics does not translate easily into effective changes

Expanding the Horizons of Manufacturing: Towards Wide Integration, Smart Systems and Tools

This research topic aims at enterprise-wide modeling and optimization (EWMO) through the development and application of integrated modeling, simulation and optimization methodologies, and computer-aided tools for reliable and sustainable improvement opportunities within the entire manufacturing network (raw materials, production plants, distribution, retailers, and customers) and its components. This integrated approach incorporates information from the local primary control and supervisory modules into the scheduling/planning formulation. That makes it possible to dynamically react to incidents that occur in the network components at the appropriate decision-making level, requiring fewer resources, emitting less waste, and allowing for better responsiveness in changing market requirements and operational variations, reducing cost, waste, energy consumption and environmental impact, and increasing the benefits. More recently, the exploitation of new technology integration, such as through semantic models in formal knowledge models, allows for the capture and utilization of domain knowledge, human knowledge, and expert knowledge toward comprehensive intelligent management. Otherwise, the development of advanced technologies and tools, such as cyber-physical systems, the Internet of Things, the Industrial Internet of Things, Artificial Intelligence, Big Data, Cloud Computing, Blockchain, etc., have captured the attention of manufacturing enterprises toward intelligent manufacturing systems

Space resources. Volume 4: Social concerns

Space resources must be used to support life on the Moon and exploration of Mars. This volume, Social Concerns, covers some of the most important issues which must be addressed in any major program for the human exploration of space. The volume begins with a consideration of the economics and management of large scale space activities. Then the legal aspects of these activities are discussed, particularly the interpretation of treaty law with respect to the Moon and asteroids. The social and cultural issues of moving people into space are considered in detail, and the eventual emergence of a space culture different from the existing culture is envisioned. The environmental issues raised by the development of space settlements are faced. Some innovative approaches are proposed to space communities and habitats and self-sufficiency is considered along with human safety at a lunar base or outpost