Developing motion primitives for off-the-shelf robots like the Aldebaran Nao robot is cumbersome and time consuming. With our research we aim at automized development in terms of evolutionary generation and optimization of motion primitives, which in fact are motion programs. This paper describes how to apply genetic programming to the domain of robotic motion programs. For that purpose we introduce a domain specific language that can be transformed into code executed by the robots kernel, perform artificial evolution in a simulation environment as much as on real robots, and evaluate the performance increase of generated programs.

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Component based software engineering has found broad acceptance within the embedded systems community over the last years. However, to fully exploit its potential in terms of reusability and cost-efficiency, existing code-bases have to be refactored in a component based way. To support refactorization, static analysis techniques can be used to identify components within coarse-grained layered or even monolithic legacy software for embedded systems. We present an approach for semi-automatic extraction of components from automotive software and compare two different versions, one type-based component-recognition analysis of linear complexity with a more precise version based on a points-to analysis of almost linear algorithmic complexity. Both analyses are applied to an industrial implementation of an automotive communication stack. Each analysis is evaluated with two sets of additional manually created annotations of distinct size and precision. Thus, both analyses are fully evaluated in terms of execution-time, memory consumption and analysis precision, and its impact on the number of recognized components. We show that the more precise analysis allows the use of a smaller user-provided filter set and obtain a more fine-grained component recognition.

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Mobile autonomous robots are systems that on the one hand are seriously constricted to processing power, energy consumption and execution time, but on the other hand typically have to issue strict safety guarantees. A robot must consume as little power and CPU cycles as possible in order to maximize its sustainability but also its reactivity. In addition, a robot has to operate under strict safety conditions as it might inflict serious damage to the real world or even human beings. Safety properties in robotic software are often proven at source code or even model level. A well established methodology for improving execution time and energy consumption is that of compiler optimization. When translating a given program into machine executable code, an optimizing compiler transforms the original program into an improved but semantically equivalent one. Unfortunately, safety properties specified and verified at source code level might be violated in a transformed program. Hence, aggressive compiler optimization is not suitable for state-of-the-art safety-critical robotic systems. This paper outlines ongoing work on optimizing compilers that perform translation validation for all executed program transformations. Consequently, the outcome of optimizing transformations is formally verified and therefore can be applied to safety-critical robotic systems.

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Autonomous mobile robots are devices that operate within a highly indeterministic environment, the real world. Even worse, robots are physical devices that are part of the real world and hence are inherently nondeterministic by construction w.r.t. mechanical precision and sensor noise. In consequence, robotic control software has to cope with discrepancies between a robot's specification and its de-facto physical properties as achieved in production. Finding feasible parameters for robust motion controllers is a time consuming and cumbersome work. This paper contributes by demonstrating how to utilize an evolutionary process, a genetic algorithm, to automatically find terrain specific optimized parameter sets for off-the-shelf motion controllers of humanoid robots. Evolution is performed within a physical accurate simulation in order to speed up and automate the process of parameter acquisition, while results are devolved to the real devices that benefit noticeably.

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Progress in robotics has led to complex autonomous and even collaborating robotic systems, fulfilling mission critical tasks in safety critical environments. An increase in capabilities and thus complexity consequently led to a dramatic increase in possible faults that might manifest in errors. Even worse, by applying robots with emerging behavior in non-deterministic real-world environments, faults may be introduced from external sources. Consequently, fault testing has become increasingly difficult. Both, software and hardware may fail or even break, and hence may cause a mission failure, heavy damage, or even severe injuries and loss of life. The ability of a robotic system to function in presence of such faults, so to become fault tolerant, is a continuously growing area of research. Our work meets this challenge by developing a mechanism for robotic systems that is capable of detecting defects, selecting feasible counter measures, and hence keeping robots in a sane and and consequently safe state. Inspired by biology, we conceptually aim at an immune system for a robot (RIS), which is able to detect anomalies, and which is able to autonomously counter them by appropriate means. This position paper outlines the requirements and research scopes that have been identified as relevant for the development of a robotic immune system.

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Progress in robotics has led to complex autonomous robotic systems, fulfilling mission critical tasks in safety critical environments. Besides classical robotic tasks in automation and tele-operation, todays applications of robotic systems range from search and rescue, over explorative deep see or space exploration, up to autonomous navigating of vehicles in public areas. Unfortunately, increase in capabilities and thus complexity has also led to a dramatic increase in possible faults that might manifest in errors. Even worse, by applying robots with emerging behavior in non-deterministic real-world environments, faults may be introduced from external sources. Consequently, fault testing has become increasingly difficult. Both, software and hardware may fail or even break, and hence may cause a mission failure, heavy damage, or even severe injuries and loss of lifes. The ability of a robotic system to function in presence of such faults, so to become fault tolerant, is a continuously growing area of research. Our work meets this challenge by developing a mechanism for robotic systems that is capable of detecting defects, selecting feasible counter measures, and hence keeping robots in a sane and and consequently safe state. Inspired by biology, we conceptually build an immune system for a robot, which is able to detect anomalies, and which is able to autonomously counter them by appropriate means.

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Software development for state-of-the-art autonomous robots has to face complex hardware architectures in conjunction with complex algorithms and dynamic environments. In consequence, developers have to master concurrency in highly distributed systems with traditional development methodologies. Unfortunately, this fact leads to high costs for proper development or erroneous software. We propose a model driven methodology that automatically generates synchronization as much as guarding artifacts where required, removing the burden of detecting race conditions in concurrent threads of execution from the developer by utilizing system models and model transformations.

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Current and upcoming robotic systems have to fulfill mission and safety critical tasks within real world environments. Robots like unmanned underwater vehicles and autonomous vehicles for space exploration require long-term autonomy, others like intelligent vehicles and mobile domestic robots have to closely collaborate with human individuals. Consequently, robotic system software has to be reliable and safe. Moreover, state-of-the-art robotic software is highly reactive, inherently parallel, distributed, and operating in real-time. Hence, it is complex, hard to develop, and even harder to certify. Our work aims at an improved software development methodology that on the one hand allows high level development of certifiable robotic software and on the other hand is capable of synthesizing optimized low-level code for robust concurrent real-time environments. To reach this goal we rely on methodologies based on timed automata and on static tokens to semi-automatically guarantee the absence of resource conflicts.

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Code-level timing analysis, such as Worst-Case Execution Time (WCET) analysis, takes place at the binary level. However, much information that is important for the analysis, such as constraints on possible program flows, are easier to derive at the source code level since this code contains much more information. Therefore, different source-level analyses can provide valuable support for timing analysis. However, source-level analysis is not always smoothly applicable in industrial projects. In this paper we report on the experiences of applying source-level analysis to industrial code in the ALL-TIMES FP7 project: the promises, the pitfalls, and the workarounds that were developed. We also discuss various approaches to how the difficulties that were encountered can be tackled.

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Driven by steadily increasing requirements of innovative applications, automotive electronics has evolved into highly dependable, distributed, real-time embedded systems. To close the rising gap between increasing complexity and affordable costs, the upcoming automotive software standard AUTOSAR constitutes Component Based Software Engineering (CBSE) as development methodology for future automotive applications. CBSE introduces a clear separation of concerns into AUTOSAR's system architecture: Any application is built from reusable and exchangeable so called Software Components that deal with business logic only, whereas standardized infrastructural services are provided by component middleware - the AUTOSAR Basic Software and the AUTOSAR Run Time Environment. This design leads to an increase in reusability, maintainability, and application quality, and hence to a reduction of costs and time-to-market. However, AUTOSAR component middleware is specified as layered software architecture that is customizable on a coarse-grained level only, and thus tends to be heavy-weight and impractical in resource constrained embedded systems. This thesis contributes by extending the scope of Component Based SOftware Engineering within AUTOSAR beyond the application layer to the component middleware, especially to its communication subsystem. In a first step, the layered AUTOSAR middleware architecture is replaced by a component based design that is extracted from an existing layered reference implementation by static analysis - the Cohesion Analysis. The proposed component based communication middleware completely resembles the standard's functionality, but is more flexible in terms of application specific customization. In addition, use-case based variants of identified component classes are defined to enable improved middleware optimization. In a second step, a model transformation for AUTOSAR application models is specified that enables automatic middleware synthesis in line with the AUTOSAR methodology. The Connector Transformation injects middleware component architectures in place of all explicit connectors within the application models. Thereby, platform-specific models for each system node are generated, which completely and solely reflect the application's middleware requirements. To evaluate the proposed approach, it is applied to a simple automotive application. The hereby gained synthesized communication middleware shows an improvement of nearly 30% with respect to its memory footprint and a reduction in CPU usage of up to 10% compared to its conventional counterpart.

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Distributed real-time automotive embedded systems have to be highly dependable as well as cost-efficient due to the large number of manufactured units. To close the gap between raising complexity and cutting costs, upcoming software standards like AUTOSAR introduce a clear separation of concerns into their system architecture. An AUTOSAR application is built from components that deal with business logic only whereas infrastructural services are provided by standardized middleware. Unfortunately, this middleware tends to be heavy-weight due to its coarse-grained layered design. By applying a component based design to AUTOSAR's middleware, a custom-tailored version for each specific application and system node can be built to overcome this problem. This paper demonstrates how to automatically synthesize component based middleware via the Connector Transformation: Component connectors in platform independent application models are utilized to automatically assemble platform- and application specific middleware. As a result, AUTOSAR middleware becomes custom-tailored and hence light-weight and flexible. In addition, the described synthesis algorithm is capable of incorporating timing annotations via interface contracts at model level, and thus reflects upcoming ambitions to cover real-time constraints at middleware level within AUTOSAR. To prove our approach we successfully synthesized middleware for a demonstrator application and compared it to its conventional counterpart.

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AUTOSAR as specified in its current version fosters timing-constraints at application level to support the development of real-time automotive applications. However, the standard's actual specification does not consider any timing information for its Basic Software. In consequence, the over-all timing-behavior of software running at a specific system node can not be calculated and thus validated at development-time. Even worse, any exchange or modification of Basic Software modules induces unpredictable alteration in system timing, and may even lead to a severe miss of execution deadlines. Within this paper we solve this issue by using a component based Basic Software architecture, as much as timing-aware software composition for Basic Software components. We therefore introduce timing contracts as enhancement for existing interface contracts, specify a timing annotation language on a conceptual level, and demonstrate how to capitalize on our approach by calculating timings within composed Basic Software architectures at development time.

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Current trends in embedded systems software aim at an increase of reusability, exchangeability and maintainability and thus at a significant reduction of time- and costs-to-market. One way to reach these goals is the adaption of Component Based Software Engineering (CBSE) for the embedded systems domain. Unfortunately most existing embedded systems applications are realized as coarse-grained layered or even monolithic software that can hardly be reused. This paper demonstrates how to recognize reusable and exchangeable components within existing typically monolithic or stacked embedded systems software via a semi-automatic analysis of the system's source code. The complexity of the proposed analysis is kept linear to code size by utilizing expert-knowledge on the application-domain, and deployment specific configuration data. To prove our approach, a functional decomposition for an existing automotive middleware stack is calculated and is finally compared to a human designed one.

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Current trends in embedded systems software for the automotive domain aim at an increase of reusability, exchangeability and maintainability, and thus at a significant reduction of time- and costs-to-market. One way to reach these goals is the adaption of Component Based Software Engineering (CBSE) for resource constrained embedded systems. The Automotive Open System Architecture (AUTOSAR), an upcoming industry standard within the automotive domain, reflects this fact by constituting CBSE as development paradigm for automotive applications: Application concerns are covered by software components, while infrastructural ones are handled within layered component middleware - the AUTOSAR Runtime Environment (RTE) and the Basic Software (BSW). However, the AUTOSAR Basic Software itself is specified as layered architecture that is only customizable on a coarse-grained level, and thus tends to be heavy-weight and less flexible. Therefore, this paper contributes by applying the component paradigm to the AUTOSAR BSW, to improve the capabilities of standard compliant software systems. The redesigned BSW externally provides all interfaces to the RTE prescribed by AUTOSAR, whereas the BSW's internal architecture is fully component based.

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Interaction in distributed component based architectures can become a rather complex and error prone issue. As it is good practice to keep application concerns separated from infrastructural ones, component based applications typically rely on communication middleware to cope with matters of distributed heterogeneous interaction. Unfortunately, generic middleware tends to be monolithic, heavyweight software which is unacceptable in resource constrained embedded systems. Communication middleware for distributed embedded systems has to be custom tailored to the application’s interaction needs and therefore shall be as lightweight as possible. By applying the component paradigm to the communication middleware and introducing connectors as first class architectural entities, it becomes feasible to automatically synthesize application specific middleware from the application’s architectural models and a set of prefabricated communication primitives. We contribute by specifying these structural designs for explicit connectors and by identifying the classes of their basic building blocks, thus providing a sound foundation for middleware synthesis.

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The number of electronic systems in cars is continuously growing. Electronic systems, consisting of so-called electronic control units (ECUs) interconnected by a communication network, account for up to 30% of a modern car’s worth. Consequently, software plays an ever more important role, both for the implementation of functions and the infrastructure. In order to benefit from the reuse of software modules, the major automotive companies have standardized a large number of these modules in the context of the AUTOSAR consortium. In this paper we propose the refactoring of the AUTOSAR stack of system software modules by applying the componentbased paradigm in order to increase the scalability of the software stack according to the requirements of the application. We demonstrate the feasibility of this approach by performing the refactoring of the modules FlexRay Driver and FlexRay Interface as an example and by deploying the resulting refactored components in a sample automotive application. Finally we measure the execution time as well as the memory consumption of the refactored components and compare these measures to the measures obtained from the corresponding ordinary AUTOSAR modules

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To reduce time and cost to market of automotive software systems and simultaneously increase the products’ quality, the component paradigm has found broad acceptance within the automotive industry over the last few years. This fact is reflected by upcoming domain specific software standards like AUTOSAR. In AUTOSAR application concerns are covered by software components, while infrastructural ones are handled within layered component middleware. The so gained separation of concerns leads to an increase in application quality, reusability and maintainability, and hence to a reduction of cost and time to market. This paper contributes with the consequent application of the component paradigm to AUTOSAR’s layered middleware, thereby gaining all benefits of CBSE not only for the application level but for the whole automotive software system. The introduced component model for middleware components can flexibly be used to build resource-aware, AUTOSAR compliant, component middleware for distributed automotive software systems and can seamlessly be integrated within the AUTOSAR system architecture.

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During the last years, component based software development has become a well accepted software engineering paradigm within the automotive industry. This fact is not only reflected by upcoming development tools but also by newly arising automotive software standards. In component based software engineering, applications are built by assembling small reusable building blocks, the components. Typically more than one component implementation meets the application developer's requirements, so proper selection of the assembled components becomes a key element of the whole procurement and engineering process. This paper's contribution is twofold: First, a basic set of performance and dependability metrics and measures for automotive components is identified. Second, a unified benchmarking process is proposed, that allows an unambiguous comparison of distinct component implementations of a given component class.

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In component based software engineering, an application is build by composing trusted and reusable units of execution, the components. A composition is formed by connecting two components' related interfaces. The point of connection, namely the connector, is an abstract representation of their interaction. Most component models' implementations rely on extensive middleware, which handles component interaction and hides matters of heterogeneity and distribution from the application components. In resource constrained embedded systems this middleware and its resource demands are a key factor for the acceptance and usability of component based software. By addressing connectors as first class architectural entities at model level, all program logic related to interaction can be located within them. Therefore the set of all explicit connectors of a component architecture denotes the exact requirements of that application's communication and interaction needs. We contribute by demonstrating how to use explicit connectors in model driven development to synthesize a custom tailored, component based communication middleware. This synthesis is achieved by model transformations and optimizations using prefabricated basic building blocks for communication primitives.

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When building a system by connecting components, the connection itself, the connector, becomes a hot-spot of abstraction for any interaction. In contrary to most existing component models, we introduce explicit connectors as first class architectural entities. They materialize detailed contracts regarding composition, deployment and interaction and hence provide fine granular information on composed structures. Using explicit connectors results in customtailored and consequently light-weight middleware, as any interaction logic is contained within them. Modeling component architectures with explicit connectors allows the usage of off-the-shelf connector libraries. Thereby, developing a distributed component based application becomes less complex and more competitive due to reduced costs and increased reliability. We contribute by adopting a model driven development process for the use of explicit connectors by extending the syntax of UML 2.0 and defining a set of required model transformations.

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The increasing complexity of today's embedded systems applications imposes the requirements and constraints of distributed, heterogeneous subsystem interaction to software engineers. These requirements are well met by the component based software engineering paradigm: complex software is decomposed into coherent, interacting units of execution, the so called components. Connectors are a commonly used abstraction to model the interaction between them. We consequently contribute with the application of explicit connectors for distributed embedded systems software. Explicit connectors encapsulate the logic of distributed interaction, hence they provide well defined contracts regarding properties of inter-component communication. Our approach allows model level validation of component composition and interaction incorporating communication related constraints beyond simple interface matching. In addition, by using explicit connectors, the complexity of application components is reduced without the need for any heavy weight middleware. In fact, the set of all deployed explicit connectors forms the smallest possible, custom tailored middleware.

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When building a component based application for distributed embedded systems, its overall behavior depends not only on the contracts applying to the components and their interfaces, but even more so on explicit as well as implicit connectors emerging from component composition, deployment and interaction. Explicit connectors provide additional contracts on resource requirements and information channels. We contribute by showing how to perform model level validation of component and contract composition beyond simple interface matching. Moreover, we discuss a classification of typical component connectors to simplify application development for distributed embedded systems. This avoids the need of extensive knowledge of communication subsystems and the existence of any heavy weight middle-ware.

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The significant increase in demand for mobile autonomous robots over the last few years has led to a boost in research and development in the fields of artificial intelligence and robotics. This thesis proposes an architecture for a flexible extendable and scaleable artificial intelligence for robotic soccer as simplified environment of a Multi Agent Domain. The architecture is based on the physiological functionality of the central nervous system of animals and therefore supports highly parallel, loosely coupled, asynchronous subsystems. A software design paradigm has been developed to meet the requirements imposed by these considerations. The architecture provides a launchpad for scientific research, and allows the development of state-of-the-art artificial intelligence for robotic soccer competitions.

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