12 research outputs found

    A Survey on Domain-Specific Modeling and Languages in Robotics

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    Nordmann A, Hochgeschwender N, Wigand DL, Wrede S. A Survey on Domain-Specific Modeling and Languages in Robotics. Journal of Software Engineering in Robotics. 2016;7(1):75-99

    Reversible Computation: Extending Horizons of Computing

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    This open access State-of-the-Art Survey presents the main recent scientific outcomes in the area of reversible computation, focusing on those that have emerged during COST Action IC1405 "Reversible Computation - Extending Horizons of Computing", a European research network that operated from May 2015 to April 2019. Reversible computation is a new paradigm that extends the traditional forwards-only mode of computation with the ability to execute in reverse, so that computation can run backwards as easily and naturally as forwards. It aims to deliver novel computing devices and software, and to enhance existing systems by equipping them with reversibility. There are many potential applications of reversible computation, including languages and software tools for reliable and recovery-oriented distributed systems and revolutionary reversible logic gates and circuits, but they can only be realized and have lasting effect if conceptual and firm theoretical foundations are established first

    Reversible Computation: Extending Horizons of Computing

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    This open access State-of-the-Art Survey presents the main recent scientific outcomes in the area of reversible computation, focusing on those that have emerged during COST Action IC1405 "Reversible Computation - Extending Horizons of Computing", a European research network that operated from May 2015 to April 2019. Reversible computation is a new paradigm that extends the traditional forwards-only mode of computation with the ability to execute in reverse, so that computation can run backwards as easily and naturally as forwards. It aims to deliver novel computing devices and software, and to enhance existing systems by equipping them with reversibility. There are many potential applications of reversible computation, including languages and software tools for reliable and recovery-oriented distributed systems and revolutionary reversible logic gates and circuits, but they can only be realized and have lasting effect if conceptual and firm theoretical foundations are established first

    Temporal Reasoning About Robotics Applications: Refinement and Temporal Logic

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    The challenges of verifying the behaviour of robotics systems has motivated the development of various techniques and tools for supporting the advancement and verification of robotics systems. This is due to the complex nature of verifying robotics systems as part of the category of hybrid dynamical systems that combine discrete and continuous parts. In contrast to the commonly-known computer systems, robotic sys- tems operate in a physical, real-world environment that may include humans, which raises a reasonable question of concern about the safety of the systems. Currently, one of the promising solutions is effective, rigorous verification techniques and tools that verify and guarantee the safe operation of robotics systems. Along this line, formal methods provide mathematical models that support the de- velopment of rigorous verification techniques and tools. In this work, we use formal methods for the verification of temporal specifications of robotics systems. The process algebra tock-CSP provides textual notations for modelling discrete-time behaviours, with the support of various tools for verification. Also, tock-CSP has been used to give semantics to a domain-specific language for robotics, RoboChart. Similarly, automatic verification of Timed Automata (TA) is supported by the real-time verification toolbox Uppaal that facilitates verification of temporal specifications using Time Computation Tree Logic (TCTL). Timed Automata and tock-CSP differ in both modelling and verification approaches. For instance, liveness requirements are difficult to specify with the constructs of tock-CSP, but they are easy to verify in Uppaal. In this work, we add a step forward in translating tock-CSP into TA to take advantage of Uppaal. We have developed a translation technique and tool; our work uses rules for translating tock-CSP into a network of small TAs, which address the complexity of capturing the compositionality of tock-CSP. For the validation of our proposed con- tributions, we use an experimental approach based on finite approximations to trace sets. We consider trace semantics for validating the translation technique. Thus, we develop a technique for generating and comparing traces of tock-CSP and TA. In order to evaluate the translation technique and its corresponding tool, we use two forms of test cases: a large collection of small processes and case studies from the literature. We illustrate a plan for using mathematical proof to establish the correctness of the rules that will cover an infinite set of traces

    Lidar-based Obstacle Detection and Recognition for Autonomous Agricultural Vehicles

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    Today, agricultural vehicles are available that can drive autonomously and follow exact route plans more precisely than human operators. Combined with advancements in precision agriculture, autonomous agricultural robots can reduce manual labor, improve workflow, and optimize yield. However, as of today, human operators are still required for monitoring the environment and acting upon potential obstacles in front of the vehicle. To eliminate this need, safety must be ensured by accurate and reliable obstacle detection and avoidance systems.In this thesis, lidar-based obstacle detection and recognition in agricultural environments has been investigated. A rotating multi-beam lidar generating 3D point clouds was used for point-wise classification of agricultural scenes, while multi-modal fusion with cameras and radar was used to increase performance and robustness. Two research perception platforms were presented and used for data acquisition. The proposed methods were all evaluated on recorded datasets that represented a wide range of realistic agricultural environments and included both static and dynamic obstacles.For 3D point cloud classification, two methods were proposed for handling density variations during feature extraction. One method outperformed a frequently used generic 3D feature descriptor, whereas the other method showed promising preliminary results using deep learning on 2D range images. For multi-modal fusion, four methods were proposed for combining lidar with color camera, thermal camera, and radar. Gradual improvements in classification accuracy were seen, as spatial, temporal, and multi-modal relationships were introduced in the models. Finally, occupancy grid mapping was used to fuse and map detections globally, and runtime obstacle detection was applied on mapped detections along the vehicle path, thus simulating an actual traversal.The proposed methods serve as a first step towards full autonomy for agricultural vehicles. The study has thus shown that recent advancements in autonomous driving can be transferred to the agricultural domain, when accurate distinctions are made between obstacles and processable vegetation. Future research in the domain has further been facilitated with the release of the multi-modal obstacle dataset, FieldSAFE

    Framework-level resource awareness in robotics and intelligent systems. Improving dependability by exploiting knowledge about system resources

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    Wienke J. Framework-level resource awareness in robotics and intelligent systems. Improving dependability by exploiting knowledge about system resources. Bielefeld: Universität Bielefeld; 2018.Modern robots have evolved to complex hardware and software systems. As such, their construction and maintenance have become more challenging and the potential for failures has increased. These failures and the resulting reduction of dependability have a considerable effect on the acceptance and usefulness of robotics systems in their intended applications. Even though different software engineering techniques have been developed to control dependability-critical aspects of such complex systems, the state of the art for experimental robotics and intelligent systems is that – if at all – functional properties are systematically controlled though techniques such as unit testing and simulation runs. Yet, system dependability can also be impaired if nonfunctional properties behave unexpectedly. This thesis focuses on the utilization of system resources such as CPU, memory, or network bandwidth as an important nonfunctional aspect, which has not received much systematic treatment in robotics and intelligent systems so far. Unexpected utilizations of system resources can have effects ranging from merely wasting energy and reducing a robot’s operational time to a degradation in its function due to processing delays. Even safety-critical situations can arise, for instance, if a motion planner or obstacle avoidance component cannot react before a collision. Therefore, the systematic analysis of a system’s resource utilization, a guidance of developers regarding these aspects, and testing and fault detection for unexpected resource utilization patterns are an effective contribution of this thesis towards more reliable robots. In this work I describe a concept for integrating resource awareness into component-based robotics and intelligent systems. This concept specifically addresses the often loosely controlled development process predominant in experimental research. As such, the presented methods have to be applicable without a high overhead or large changes to the evolved development methods and system structures. Within this concept, which I termed framework-level resource awareness, I have explored methods in two directions: On the one hand, a set of tools helps developers to understand and systematically control the resource utilization while developing and testing systems. On the other hand, I have applied machine learning techniques to enable autonomous reactions at runtime based on predictions about the resource utilization of system components. With the two views, this work explores novel directions for implementing resource awareness in research systems and the conducted evaluations underline the suitability of the framework-level resource awareness concept

    Model Driven Development of Sensor Web Networks Architecture

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    Primjena Internet protokola u uređajima sa ograničenim resursima, dovodi do radikalne promjene Interneta i pojave potpuno novog koncepta pod nazivom Internet stvâri – Internet of Things (IoT), čiji je jedan od osnovnih gradivnih elemenata Senzor Web (SW) čvor. SW čvor predstavlja elementarni “resurs” u SW mreži koja se po svojoj prirodi može posmatrati kao nestrukturirana kolekcija gradivnih elemenata koji se mogu dinamički orkestrirati u virtuelne klastere, odnosno u arhi-tekturu. Cilj disertacije predstavlja unapređenje procesa razvoja arhitekture sistema baziranih na SW mrežama uz oslonac na dinamičko generisanje servisnog sloja u svrhu povećanja produktivnosti, održivosti i smanjenja troškova razvoja. Pod unapređenjem procesa razvoja arhitekture smatra se analiza, integracija i prilagođavanje postojećih sistema i pristupa projektovanja arhitekture senzorskih mreža, kao i sistema baziranih na IoT konceptima. U tu svrhu definisana je arhitektura SW mreža, kreiran domenski specifičan jezik, interaktivni grafički editor i alat za automatsku transforma-ciju modela u implementacione klase. U sklopu teze izvršena je i eksperimentalna verifikacija predloženog modela i razvojnog okruženja, čime je dokazana njhova praktična primjena.The use of Internet protocols in limited resources devices contributes to radical changes in the Internet and the emergence of an entirely new concept called the Internet of Things (IoT), consisted of the Sensor Web (SW) nodes as one of the basic building blocks. SW node is the elementary "resource" in the SW Network, which by their nature can be seen as an unstructured collection of blocks that can be dynamically orchestrated into the virtual cluster, or in the architecture. The aim of this thesis is to improve the process of developing a system archite-cture based on SW networks, relying on the dynamic generation of the service layer in order to increase productivity, sustainability and cost of development. The improvement of the architecture development process includes analysis, integration and adaptation of existing systems and sensor network architecture design approaches, as well as systems based on the IoT concepts. For this purpose, the archite-cture of the SW Network is defined, a domain-specific language has been created as well as interactive graphics editor and a tool for automatic transformation of models into the implementation class. As part of the dissertation, the experimental verification of the proposed model and the development environment were carried out demonstra-ting their practical application

    Proceedings of the Fifth International Workshop on Domain-Specific Languages and Models for Robotic Systems (DSLRob 2014)

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    The Fifth International Workshop on Domain-Specific Languages and Models for Robotic Systems (DSLRob'14) was held in conjunction with the 2014 International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR 2014), October 2014 in Bergamo, Italy. The main topics of the workshop were Domain-Specific Languages (DSLs) and Model-driven Software Development (MDSD) for robotics. A domain-specific language is a programming language dedicated to a particular problem domain that offers specific notations and abstractions that increase programmer productivity within that domain. Model-driven software development offers a high-level way for domain users to specify the functionality of their system at the right level of abstraction. DSLs and models have historically been used for programming complex systems. However recently they have garnered interest as a separate field of study. Robotic systems blend hardware and software in a holistic way that intrinsically raises many crosscutting concerns (concurrency, uncertainty, time constraints, ...), for which reason, traditional general-purpose languages often lead to a poor fit between the language features and the implementation requirements. DSLs and models offer a powerful, systematic way to overcome this problem, enabling the programmer to quickly and precisely implement novel software solutions to complex problems within the robotics domain

    WICC 2017 : XIX Workshop de Investigadores en Ciencias de la Computación

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    Actas del XIX Workshop de Investigadores en Ciencias de la Computación (WICC 2017), realizado en el Instituto Tecnológico de Buenos Aires (ITBA), el 27 y 28 de abril de 2017.Red de Universidades con Carreras en Informática (RedUNCI
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