| 201. |
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| 202. |
- Kraft, Johan, et al.
(författare)
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Continuous Constant-Memory Monitoring of Embedded Software Timing
- 2011
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Ingår i: 2nd International Workshop on Analysis Tools and Methodologies for Embedded and Real-time Systems (WATERS'11), satellite workshop of EUROMICRO Conference on Real-Time Systems (ECRTS'11).
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Konferensbidrag (refereegranskat)abstract
- A method is presented for generating statistical models of timing data continuously over very long monitoring sessions. This method is intended for memory-efficient runtime modeling of timing properties in embedded software systems, such as execution times or inter-arrival times, but is a quite generic method that should be applicable for other purposes and domains as well. Specifically, we intend to use this method as a component in automatic generation of simulation models for probabilistic timing analysis of complex embedded software systems. Given a stream of data as input, this method gradually builds up a statistical model capturing the approximate distribution of the data. The method uses a modest and fixed amount of on-target RAM, decided by the desired accuracy of the model, and allows for long monitoring sessions covering billions of data points. The paper presents the motivation, algorithm, a prototype implementation and evaluation using real execution time data from an ARM7 microcontroller.
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| 203. |
- Kraft, Johan, et al.
(författare)
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Software Maintenance Research in the PROGRESS Project for Predictable Embedded Software Systems
- 2011
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Ingår i: 15th European Conference on Software Maintenance and Reengineering (CSMR'11). - Los Alamitos : IEEE Computer Society. - 9780769543437 ; , s. 335-338
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Konferensbidrag (refereegranskat)abstract
- PROGRESS is a project and strategic research centre at Malardalen University in Sweden that is funded for 2006-2010 by the Swedish Foundation for Strategic Research (SSF). PROGRESS research targets embedded software in the vehicular, automation, and telecom domains, focusing on the areas of component technology, verification and analysis for predictability, predictable execution, as well as reuse and maintenance of legacy embedded software. We first describe the funding, organization and research areas of PROGRESS, and then give several examples of PROGRESS research that addresses maintenance of legacy embedded software with the goal to improve program comprehension, quality assurance, and debugging. Specifically, we describe research in tracing and trace visualization, impact analysis of temporal behavior, slicing, and system-specific static analyses.
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| 204. |
- Lager, Anders, et al.
(författare)
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A Scalable Heuristic for Mission Planning of Mobile Robot Teams
- 2023
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Ingår i: IFAC-PapersOnLine. - : Elsevier B.V.. - 9781713872344 ; , s. 7865-7872
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Konferensbidrag (refereegranskat)abstract
- In this work, we investigate a task planning problem for assigning and planning a mobile robot team to jointly perform a kitting application with alternative task locations. To this end, the application is modeled as a Robot Task Scheduling Graph and the planning problem is modeled as a Mixed Integer Linear Program (MILP). We propose a heuristic approach to solve the problem with a practically useful performance in terms of scalability and computation time. The experimental evaluation shows that our heuristic approach is able to find efficient plans, in comparison with both optimal and non-optimal MILP solutions, in a fraction of the planning time.
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| 205. |
- Lager, Anders, et al.
(författare)
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A Task Modelling Formalism for Industrial Mobile Robot Applications
- 2021
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Ingår i: 2021 20th International Conference on Advanced Robotics, ICAR 2021. - : Institute of Electrical and Electronics Engineers Inc.. - 9781665436847 ; , s. 296-303
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Konferensbidrag (refereegranskat)abstract
- Industrial mobile robots are increasingly introduced in factories and warehouses. These environments are becoming more dynamic with human co-workers and other uncertainties that may interfere with the robot's actions. To uphold efficient operation, the robots should be able to autonomously plan and replan the order of their tasks. On the other hand, the robot's actions should be predictable in an industrial process. We believe the deployment and operation of robots become more robust if the experts of the industrial processes are able to understand and modify the robot's behaviour. To this end, we present an intuitive novel task modelling formalism, Robot Task Scheduling Graph (RTSG). RTSG provides building blocks for the explicit definition of alternative task sequences in a compact graph format. We present how such a graph is automatically converted to a task planning problem in two different forms, i.e., a Mixed Integer Linear Program (MILP) and a Planning Domain Definition Language specification (PDDL). Converted RTSG models of a mobile kitting application are used to experimentally compare the performance of one MILP planner and two PDDL planners. Besides providing this comparison, the experiments confirm the equivalence of the converted MILP and PDDL problem formulations. Finally, a simulation experiment verifies the assumed correlation between a cost model, based on path lengths, and the makespan.
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| 206. |
- Lager, Anders, et al.
(författare)
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IoT and Fog Analytics for Industrial Robot Applications
- 2020
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Ingår i: The 25th International Conference on Emerging Technologies and Factory Automation ETFA2020.
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Konferensbidrag (refereegranskat)abstract
- The rapid development of IoT, cloud and fog computing has increased the potential for developing smart services for IoT devices. Such services require not only connectivity and high computing capacity, but also fast response time and throughput of inferencing results. In this paper we present our ongoing work, investigating the potential for implementing smart services in the context of industrial robot applications with focus on analytic inferencing on fog and cloud computing platforms. We review different use cases that we have found in the literature and we divide them into two suggested categories, "distributed deep models" and "distributed interconnected models". We analyze the characteristics of IoT data in industrial robot applications and present two concrete use cases of smart services where inferencing in a fog and a cloud architecture, respectively, is needed. We also reason about important considerations and design decisions for the development process of analytic services.
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| 207. |
- Lager, Anders, et al.
(författare)
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Task Roadmaps: Speeding up Task Replanning
- 2022
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Ingår i: Frontiers in Robotics and AI. - : Frontiers Media SA. - 2296-9144. ; 9
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Tidskriftsartikel (refereegranskat)abstract
- Modern industrial robots are increasingly deployed in dynamic environments, where unpredictable events are expected to impact the robot's operation. Under these conditions, runtime task replanning is required to avoid failures and unnecessary stops, while keeping up productivity. Task replanning is a long-sighted complement to path replanning, which is mostly concerned with avoiding unexpected obstacles that can lead to potentially unsafe situations. This paper focuses on task replanning as a way to dynamically adjust the robot behaviour to the continuously evolving environment in which it is deployed. Analogously to probabilistic roadmaps used in path planning, we propose the concept of Task roadmaps as a method to replan tasks by leveraging an offline generated search space. A graph-based model of the robot application is converted to a task scheduling problem to be solved by a proposed Branch and Bound (B&B) approach and two benchmark approaches: Mixed Integer Linear Programming (MILP) and Planning Domain Definition Language (PDDL). The B&B approach is proposed to compute the task roadmap, which is then reused to replan for unforeseeable events. The optimality and efficiency of this replanning approach are demonstrated in a simulation-based experiment with a mobile manipulator in a kitting application. In this study, the proposed B&B Task Roadmap replanning approach is significantly faster than a MILP solver and a PDDL based planner.
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| 208. |
- Lager, Anders, et al.
(författare)
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Task Roadmaps: Speeding Up Task Replanning : Corrigendum
- 2022
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Ingår i: Frontiers in Robotics and AI. - : Frontiers Media S.A.. - 2296-9144. ; 9
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Tidskriftsartikel (refereegranskat)abstract
- In the original article, Listings 1 and 2 were not included during the typesetting process and were overlooked during production. The missing listings appear below.
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| 209. |
- Lager, Anders, et al.
(författare)
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Towards Reactive Robot Applications in Dynamic Environments
- 2019
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Ingår i: The 24th IEEE Conference on Emerging Technologies and Factory Automation ETFA2019. - 9781728103037 ; , s. 1603-1606
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Konferensbidrag (refereegranskat)abstract
- Traditionally, industrial robots have been deployed in fairly static environments, to perform highly dedicated tasks. These robots perform with very high precision and throughput. However, nowadays there is an increasing demand for utilizing robots in more dynamic environments, also performing more flexible and less specialized operations — high mix/low volume. Both traditional industrial robots and force-limited robots are used in collaborative, dynamic environments. Such robot applications introduce new challenges when it comes to efficiency and robustness. In this paper, we propose an architecture for reactive multi-robot applications in the context of dynamic environments, and we analyze the main research challenges that must be tackled for its realization. A logistics use case, with robots picking customer orders from the shelves of a warehouse, is used as a running example to support the description of the key challenges.
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| 210. |
- Lagou, Vasiliki, et al.
(författare)
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Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability
- 2021
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Ingår i: Nature Communications. - : Nature Publishing Group. - 2041-1723. ; 12:1
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Tidskriftsartikel (refereegranskat)abstract
- Differences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin at IRS1 and ZNF12 loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes.
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