Oliver Denninger

Bereichsleiter

Publikationen

Buch (2)

1. Experiences with Model-driven Engineering in NeuroroboticsInfoDetails

   Hinkel, Georg and Denninger, Oliver and Krach, Sebastian and Groenda, Henning, Springer, 2016

   Model-driven engineering (MDE) has been successfully adopted in domains such as automation or embedded systems. However, in many other domains, MDE is rarely applied. In this paper, we describe our experiences of applying MDE techniques in the domain of neurorobotics -- a combination of neuroscience and robotics, studying the embodiment of autonomous neural systems. In particular, we participated in the development of the Neurorobotics Platform (NRP) -- an online platform for describing and running neurorobotic experiments by coupling brain and robot simulations. We explain why MDE was chosen and discuss conceptual and technical challenges, such as inconsistent understanding of models, focus of the development and platform-barriers.

2. Applications and Rewriting of Omnigraphs – Exemplified in the Domain of MDDDetails

   Denninger, Oliver and Gelhausen, Tom and Geiß, Rubino, Springer Berlin Heidelberg, 2008

Zeitungs- oder Zeitschriftenartikel (3)

1. Connecting Artificial Brains to Robots in a Comprehensive Simulation Framework: The Neurorobotics PlatformInfoDetails

   Falotico, Egidio and Vannucci, Lorenzo and Ambrosano, Alessandro and Albanese, Ugo and Ulbrich, Stefan and Vasquez Tieck, Juan Camilo and Hinkel, Georg and Kaiser, Jacques and Peric, Igor and Denninger, Oliver and Cauli, Nino, 2017

   Combined efforts in the fields of neuroscience, computer science, and biology allowed to design biologically realistic models of the brain based on spiking neural networks. For a proper validation of these models, an embodiment in a dynamic and rich sensory environment, where the model is exposed to a realistic sensory-motor task, is needed. Due to the complexity of these brain models that, at the current stage, cannot deal with real-time constraints, it is not possible to embed them into a real-world task. Rather, the embodiment has to be simulated as well. While adequate tools exist to simulate either complex neural networks or robots and their environments, there is so far no tool that allows to easily establish a communication between brain and body models. The Neurorobotics Platform is a new web-based environment that aims to fill this gap by offering scientists and technology developers a software infrastructure allowing them to connect brain models to detailed simulations of robot bodies and environments and to use the resulting neurorobotic systems for in silico experimentation. In order to simplify the workflow and reduce the level of the required programming skills, the platform provides editors for the specification of experimental sequences and conditions, environments, robots, and brain–body connectors. In addition to that, a variety of existing robots and environments are provided. This work presents the architecture of the first release of the Neurorobotics Platform developed in subproject 10 “Neurorobotics” of the Human Brain Project (HBP).¹ At the current state, the Neurorobotics Platform allows researchers to design and run basic experiments in neurorobotics using simulated robots and simulated environments linked to simplified versions of brain models. We illustrate the capabilities of the platform with three example experiments: a Braitenberg task implemented on a mobile robot, a sensory-motor learning task based on a robotic controller, and a visual tracking embedding a retina model on the iCub humanoid robot. These use-cases allow to assess the applicability of the Neurorobotics Platform for robotic tasks as well as in neuroscientific experiments.

2. A Framework for Coupled Simulations of Robots and Spiking Neuronal NetworksInfoDetails

   Hinkel, Georg and Groenda, Henning and Krach, Sebastian and Vannucci, Lorenzo and Denninger, Oliver and Cauli, Nino and Ulbrich, Stefan and Roennau, Arne and Falotico, Egidio and Gewaltig, Marc-Oliver and Knoll, Alois and Dil, 2016

   Bio-inspired robots still rely on classic robot control although advances in neurophysiology allow adaptation to control as well. However, the connection of a robot to spiking neuronal networks needs adjustments for each purpose and requires frequent adaptation during an iterative development. Existing approaches cannot bridge the gap between robotics and neuroscience or do not account for frequent adaptations. The contribution of this paper is an architecture and domain-specific language (DSL) for connecting robots to spiking neuronal networks for iterative testing in simulations, allowing neuroscientists to abstract from implementation details. The framework is implemented in a web-based platform. We validate the applicability of our approach with a case study based on image processing for controlling a four-wheeled robot in an experiment setting inspired by Braitenberg vehicles.

3. Multicore-Softwarefehler im Visier: Automatische Fehlererkennung in Entwürfen paralleler ProgrammeDetails

   Frank Padberg and Oliver Denninger, 2013

Konferenzbeitrag (9)

1. Integration testing of neural robot controllers using formal experiment descriptions based on SCXMLDetails

   Krach, Sebastian Dieter and Hinkel, Georg and Denninger, Oliver, 2016

2. A visual tracking model implemented on the iCub robot as a use case for a novel neurorobotic toolkit integrating brain and physics simulationDetails

   Vannucci, Lorenzo and Ambrosano, Alessandro and Cauli, Nino and Albanese, Ugo and Falotico, Egidio and Ulbrich, Stefan and Pfotzer, Lars and Hinkel, Georg and Denninger, Oliver and Peppicelli, Daniel and others, 2015

3. A Domain-Specific Language (DSL) for Integrating Neuronal Networks in Robot ControlInfoDetails

   Hinkel, Georg and Groenda, Henning and Vannucci, Lorenzo and Denninger, Oliver and Cauli, Nino and Ulbrich, Stefan, 2015

   Although robotics has made progress with respect to adaptability and interaction in natural environments, it cannot match the capabilities of biological systems. A promising approach to solve this problem is to create biologically plausible robot controllers that use detailed neuronal networks. However, this approach yields a large gap between the neuronal network and its connection to the robot on the one side and the technical implementation on the other. Existing approaches neglect bridging this gap between disciplines and their focus on different abstractions layers but manually hand-craft the simulations. This makes the tight technical integration cumbersome and error-prone impairing round-trip validation and academic advancements. Our approach maps the problem to model-driven engineering techniques and defines a domain-specific language (DSL) for integrating biologically plausible Neuronal Networks in robot control algorithms. It provides different levels of abstraction and sets an interface standard for integration. Our approach is implemented in the Neuro-Robotics Platform (NRP) of the Human Brain Project (HBP). Its practical applicability is validated in a minimalist experiment inspired by the Braitenberg vehicles based on the simulation of a four-wheeled Husky robot controlled by a neuronal network.

4. A Stream Processing Framework for On-line Optimization of Performance and Energy Efficiency on Heterogeneous SystemsInfoDetails

   Benjamin Ranft, Oliver Denninger, Philip Pfaffe, 2014

   Modern processors have the potential of executing compute-intensive programs quickly and efficiently, but require applications to be adapted to their ever increasing parallelism. Here, heterogeneous systems add complexity by combining processing units with different characteristics. Scheduling should thus consider the performance of each processor as well as competing workloads and varying inputs. To assist programmers of stream processing applications in facing this challenge we present libHawaii, an open source library for cooperatively using all processors of heterogeneous systems easily and efficiently. It supports exploiting data flow, data element and task parallelism via pipelining, partitioning and demand-based allocation of consecutive work items. Scheduling is automatically adapted on-line to continuously optimize performance and energy efficiency. Our C++ library does not depend on specific hardware architectures or parallel computing frameworks. However, it facilitates maximizing the throughput of compatible GPUs by overlapping computations and memory transfers while maintaining low latencies. This paper describes the algorithms and implementation of libHawaii and demonstrates its usage on existing applications. We experimentally evaluate our library using two examples: General matrix multiplication (GEMM) is a simple yet important building block of many high-performance computing applications. Complementarily, the detection, extraction and matching of sparse image features exhibits greater complexity, including indeterministic memory access and synchronization.

5. On Detecting Concurrency Defects Automatically at the Design LevelInfoDetails

   Padberg, F. and Carril, L.M. and Denninger, O. and Blersch, M., 2013

   We describe an automated approach for detecting concurrency defects from design diagrams of a software, in particular, sequence diagrams. From a given sequence diagram, we automatically infer a formal, parallel specification that generalizes the communication behavior that is designed informally and incompletely in the diagram. We model-check the parallel specification against generic concurrency defect patterns. No additional specification of the software is needed. We present several case-studies to evaluate our approach. The results show that our approach is technically feasible, and effective in detecting nasty concurrency defects at the design level.

6. Recommending Relevant Code Artifacts for Change Requests Using Multiple PredictorsInfoDetails

   Oliver Denninger, 2012

   Finding code artifacts affected by a given change request is a time-consuming process in large software systems. Various approaches have been proposed to automate this activity, e.g., based on information retrieval. The performance of a particular prediction approach often highly depends on attributes like coding style or writing style of change request. Thus, we propose to use multiple prediction approaches in combination with machine learning. First experiments show that machine learning is well suitable to weight different prediction approaches for individual software projects and hence improve prediction performance.

7. Run-time Adaptation to Heterogeneous Processing Units for Real-time Stereo VisionInfoDetails

   Ranft, Benjamin and Denninger, Oliver, 2012

   Today's systems from smartphones to workstations are becoming increasingly parallel and heterogeneous: Processing units not only consist of more and more identical cores - furthermore, systems commonly contain either a discrete general-purpose GPU alongside with their CPU or even integrate both on a single chip. To benefit from this trend, software should utilize all available resources and adapt to varying configurations, including different CPU and GPU performance or competing processes. This paper investigates parallelization and adaptation strategies applied to the example application of dense stereo vision, which forms a basis i.a. for advanced driver assistance systems, robotics or gesture recognition and represents a broad range of similar computer vision methods. For this problem, task-driven as well as data element- and data flow-driven parallelization approaches are feasible. To achieve real-time performance, we first utilize data element-parallelism individually on each device. On this basis, we develop and implement strategies for cooperation between heterogeneous processing units and for automatic adaptation to the hardware available at run-time. Each approach is described concerning i.a. the propagation of data to processors and its relation to established methods. An experimental evaluation with multiple test systems reveals advantages and limitations of each strategy.

8. Case study: Parallel depth map generation from stereo imagesInfoDetails

   Oliver Denninger, Intel Labs Europe, 2010

   Multicores have conquered the server, desktop, and laptop; they will soon become the preferred choice for em-bedded systems as well. However, experience with programming multicores is lacking. Case studies could fill this gap. This paper is a case study about parallelizing depth map generation from stereo images, suitable for automotive applications. We systematically analyze several parallelization approaches and compare them on three different Intel platforms with 4, 8, and 32 cores. We utilize Pthreads, OpenMP, Intel TBB, and Intel Cilk++. Configurations with almost linear speed-up for all platforms are possible. Unfortunately, no implementation per-forms well on all platforms, and configurations chosen intuitively often perform poorly. Exploring the design space with auto-tuners would help. We conclude with recommendations for parallelizing multicore applications.

9. Game Programming and XNA in Software Engineering EducationInfoDetails

   Oliver Denninger and Jochen Schimmel, Computer Games \& Allied Technology (CGAT 08), 2008

   Game programming can help students gain practical experience with software engineering. Game programming covers a wide range of software engineering topics – including algorithms, data structures, team work, and software tools. Unfortunately, game programming usually involves many repetitive and time consuming tasks such as accessing hardware resources and managing game content. In this paper we present our experiences utilizing game programming for project courses. We discuss two conceptually different game project courses along with the results. The XNA framework relieves programmers from many of the tedious tasks mentioned, allowing them to develop a feature complete game and to gain experience with the process of software development. Students were so fascinated by the subject that they spent more time on the courses than required.

Bericht (1)

1. Fallstudie: Parallelisierung der Erstellung von Tiefenkarten aus StereobildernDetails

   Denninger, Oliver, KIT, Fakultät für Informatik, 2010

Thesis (1)

1. Erweiterung des Kantenkonzepts deklarativer Graphersetzungssysteme von Einfachkanten über Hyperkanten zu SuperkantenDetails

   Denninger, Oliver, 2007

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