| [1] | Buck, Sebastian
and Zell, Andreas. CS::APEX: A Framework for Algorithm Prototyping and Experimentation with Robotic Systems. Apr, 2018. [url]Bibtex@Article{BuckJINT2018,author = {Buck, Sebastian and Zell, Andreas}, title = {CS::APEX: A Framework for Algorithm Prototyping and Experimentation with Robotic Systems}, journal = {Journal of Intelligent {\&} Robotic Systems}, year = {2018}, month = {Apr}, day = {24}, abstract = {Robotic systems differ drastically in their sensory capabilities, their computational power and their designated tasks. For efficient algorithm development, however, we need to have a common modeling framework that enables us to generalize and re-use existing solutions. A modular approach, which is coherent across different platforms, also allows faster prototyping of new systems, given that existing functionality can be reused from already implemented modules. In this paper we develop a modeling framework based on data flow graphs that achieves the following goal: We first merge synchronous data flow and reactive programming into hybrid flow graphs, where we explicitly model synchronous and asynchronous data flow. Then we transfer concepts from finite-state machines to achieve a coherent framework which we call Activity Flow Graphs. The flow of activity enables us to model high level states directly in the data flow graph. The result is a single computation graph that can express both perception and high level control aspects of any robotic system. This theoretical foundation is the core of our open-source software framework CS::APEX, which allows the creation, manipulation and evaluation of Activity Flow Graphs and enables rapid prototyping and experimentation and can be used with any robot supporting the Robot Operating System (ROS). We then demonstrate the framework with two high level models for a fetch-and-delivery robot and a person following robot.}, issn = {1573-0409}, doi = {10.1007/s10846-018-0831-7}, url = {https://doi.org/10.1007/s10846-018-0831-7}, detailspage = {http://www.cogsys.cs.uni-tuebingen.de/publikationen/LiteraturDB/details.html?BuckJINT2018}, owner = {buck}, project = {abt_zell, robotics, patsy, csapex, csnavigation}, } |
| [2] | Adrian Zwiener and Christian Geckeler and Andreas Zell. Contact Point Localization for Articulated Manipulators with Proprioceptive Sensors and Machine Learning. In 2018 IEEE International Conference on Robotics and Automation (ICRA), pages 323-329,May, 2018. Bibtex@INPROCEEDINGS{ZwienerICRA2018,author = {Adrian Zwiener and Christian Geckeler and Andreas Zell}, booktitle = {2018 IEEE International Conference on Robotics and Automation (ICRA)}, title = {Contact Point Localization for Articulated Manipulators with Proprioceptive Sensors and Machine Learning}, year = {2018}, volume = {}, month = {May}, number = {}, pages = {323-329}, keywords = {Force;Torque;Three-dimensional displays;Robot sensing systems;Manipulator dynamics}, doi = {10.1109/ICRA.2018.8462869}, issn = {2577-087X}, timestamp = {2018.05.01}, project = {abt_zell}, } |
| [3] | Richard Hanten and Philipp Kuhlmann and Sebastian Otte and Andreas Zell. Robust Real-time 3D Person Detection for Indoor and Outdoor Applications. In {IEEE} International Conference on Robotics and Automation (ICRA), pages 2000-2006,, Brisbane, Australia,May, 2018. Bibtex@INPROCEEDINGS{2018_hanten_3dperson,title = {Robust Real-time 3D Person Detection for Indoor and Outdoor Applications}, author = {Richard Hanten and Philipp Kuhlmann and Sebastian Otte and Andreas Zell}, booktitle = {{IEEE} International Conference on Robotics and Automation (ICRA)}, address = {Brisbane, Australia}, year = {2018}, month = {May}, pages = {2000-2006}, detailspage = {http://www.cogsys.cs.uni-tuebingen.de/publikationen/LiteraturDB/details.html}, owner = {hanten}, project = {abt_zell, robotics, obstacle detection, person detection}, timestamp = {2017.10.27}, } |
| [4] | Adrian Zwiener and Sebastian Otte and Richard Hanten and Andreas Zell. Configuration Depending Crosstalk Torque
Calibration for Robotic Manipulators with Deep
Neural Regression Models. In Intelligent Autonomous Systems (IAS), The 15th International Conference on, Baden-Baden, Germany,June, 2018. Bibtex@INPROCEEDINGS{ZwienerIAS2018,title = {Configuration Depending Crosstalk Torque Calibration for Robotic Manipulators with Deep Neural Regression Models}, author = {Adrian Zwiener and Sebastian Otte and Richard Hanten and Andreas Zell}, booktitle = {Intelligent Autonomous Systems (IAS), The 15th International Conference on}, address = {Baden-Baden, Germany}, year = {2018}, month = {June}, note = {(Accepted for publication)}, detailspage = {http://www.cogsys.cs.uni-tuebingen.de/publikationen/LiteraturDB/details.html?ZwienerIAS2018}, abstract = {In this paper, an approach for articulated robotic manipulator which minimizes configuration depending crosstalk torques is presented. In particular, these crosstalk torques are an issue for the Kinova Jaco 2 manipulator. We can experimentally show that the presented approach leads to crosstalk minimization for the Kinova Jaco 2 manipulator. Crosstalk leads to a significant difference between sensor output and inverse dynamic models using CAD rigid body parameters. As a consequence, these disturbances lead to a hindered torque control and perception. Different machine learning techniques, namely Random Forests and various neural network architectures, are evaluated on this task. We show that particularly deep neural regression networks are able to learn the influence of the cross torques which improves perception.}, owner = {zwiener}, project = {abt_zell, robotics, cross torques, calibration, mashine learning}, timestamp = {2018.05.27}, } |
| [5] | Jonas Tebbe and Yapeng Gao and Marc Sastre-Rienitz and Andreas Zell. {A Table Tennis Robot System using an industrial KUKA Robot Arm}. In German Conference on Pattern Recognition (GCPR), pages ,, Stuttgart, Germany,October, 2018. Bibtex@inproceedings{TebbeGCPR2018,title = {{A Table Tennis Robot System using an industrial KUKA Robot Arm}}, author = {Jonas Tebbe and Yapeng Gao and Marc Sastre-Rienitz and Andreas Zell}, booktitle = {German Conference on Pattern Recognition (GCPR)}, pages = {}, address = {Stuttgart, Germany}, year = {2018}, month = {October}, days = {10--12}, owner = {tebbe}, project = {abt_zell, robotics}, timestamp = {2018.10.10}, doi = {10.1007/978-3-030-12939-2_3}, } |
| [6] | Cornelia Schulz and Richard Hanten and Andreas Zell. {Efficient Map Representations for Multi-Dimensional Normal Distributions Transforms}. In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 2679--2686,, Madrid, Spain,October, 2018. Bibtex@inproceedings{SchulzIROS2018,title = {{Efficient Map Representations for Multi-Dimensional Normal Distributions Transforms}}, author = {Cornelia Schulz and Richard Hanten and Andreas Zell}, booktitle = {2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, pages = {2679--2686}, address = {Madrid, Spain}, year = {2018}, month = {October}, days = {1--5}, abstract = {Efficient 2D and 3D map representations of both static and dynamic, indoor and outdoor environments are crucial for navigation of driving and flying robots. In this paper, we propose a fast and accurate approach for 2D and 3D Normal Distributions Transform (NDT) mapping based on indexed kd-trees. Similar to other approaches, we also model free space, which allows us to obtain occupancy probabilities. Additionally, we provide optional visibility based updates to enhance map consistency in case of noisy data, e.g. from stereo cameras. Unlike other available implementations, our approach is natively applicable to large-scale environments and in real-time, because our maps are able to grow dynamically. This also offers applicability to exploration tasks. To evaluate our approach, we present experimental results on publicly available datasets and discuss the mapping efficiency in terms of accuracy, runtime and memory management. As an exemplary use case, we apply our maps to Monte Carlo Localization on a well-known large-scale dataset.}, owner = {schulz}, doi = {10.1109/IROS.2018.8593602}, project = {abt_zell, robotics, ndt}, timestamp = {2018.10.05}, } |
| [7] | Ya Wang and Andreas Zell. {Improving Feature-based Visual SLAM by Semantics}. In 2018 IEEE International Conference on Image Processing, Applications and Systems (IPAS), pages 7--12,, Sophia Antipolis, France,December, 2018. Bibtex@inproceedings{WangIPAS2018,title = {{Improving Feature-based Visual SLAM by Semantics}}, author = {Ya Wang and Andreas Zell}, booktitle = {2018 IEEE International Conference on Image Processing, Applications and Systems (IPAS)}, pages = {7--12}, address = {Sophia Antipolis, France}, year = {2018}, month = {December}, days = {12--14}, owner = {wang}, doi = {10.1109/IPAS.2018.8708875}, project = {abt_zell}, timestamp = {2018.12.12}, } |
| [8] | Huski{\'c}, Goran and Buck, Sebastian and Zell, Andreas. GeRoNa: Generic Robot Navigation. , pages 1--24,2018. Bibtex@article{huskic2018gerona,title = {GeRoNa: Generic Robot Navigation}, author = {Huski{\'c}, Goran and Buck, Sebastian and Zell, Andreas}, journal = {Journal of Intelligent \& Robotic Systems}, pages = {1--24}, year = {2018}, project = {abt_zell, robotics}, publisher = {Springer}, } |