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2016


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Predictive and Self Triggering for Event-based State Estimation

Trimpe, S.

In Proceedings of the 55th IEEE Conference on Decision and Control (CDC), pages: 3098-3105, Las Vegas, NV, USA, December 2016 (inproceedings)

am ics

arXiv PDF DOI Project Page [BibTex]

2016


arXiv PDF DOI Project Page [BibTex]


Robust Gaussian Filtering using a Pseudo Measurement
Robust Gaussian Filtering using a Pseudo Measurement

Wüthrich, M., Garcia Cifuentes, C., Trimpe, S., Meier, F., Bohg, J., Issac, J., Schaal, S.

In Proceedings of the American Control Conference (ACC), Boston, MA, USA, July 2016 (inproceedings)

Abstract
Most widely-used state estimation algorithms, such as the Extended Kalman Filter and the Unscented Kalman Filter, belong to the family of Gaussian Filters (GF). Unfortunately, GFs fail if the measurement process is modelled by a fat-tailed distribution. This is a severe limitation, because thin-tailed measurement models, such as the analytically-convenient and therefore widely-used Gaussian distribution, are sensitive to outliers. In this paper, we show that mapping the measurements into a specific feature space enables any existing GF algorithm to work with fat-tailed measurement models. We find a feature function which is optimal under certain conditions. Simulation results show that the proposed method allows for robust filtering in both linear and nonlinear systems with measurements contaminated by fat-tailed noise.

am ics

Web link (url) DOI Project Page [BibTex]

Web link (url) DOI Project Page [BibTex]


Automatic {LQR} Tuning Based on {G}aussian Process Global Optimization
Automatic LQR Tuning Based on Gaussian Process Global Optimization

Marco, A., Hennig, P., Bohg, J., Schaal, S., Trimpe, S.

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages: 270-277, IEEE, IEEE International Conference on Robotics and Automation, May 2016 (inproceedings)

Abstract
This paper proposes an automatic controller tuning framework based on linear optimal control combined with Bayesian optimization. With this framework, an initial set of controller gains is automatically improved according to a pre-defined performance objective evaluated from experimental data. The underlying Bayesian optimization algorithm is Entropy Search, which represents the latent objective as a Gaussian process and constructs an explicit belief over the location of the objective minimum. This is used to maximize the information gain from each experimental evaluation. Thus, this framework shall yield improved controllers with fewer evaluations compared to alternative approaches. A seven-degree- of-freedom robot arm balancing an inverted pole is used as the experimental demonstrator. Results of a two- and four- dimensional tuning problems highlight the method’s potential for automatic controller tuning on robotic platforms.

am ics pn

Video PDF DOI Project Page [BibTex]

Video PDF DOI Project Page [BibTex]


Depth-based Object Tracking Using a Robust Gaussian Filter
Depth-based Object Tracking Using a Robust Gaussian Filter

Issac, J., Wüthrich, M., Garcia Cifuentes, C., Bohg, J., Trimpe, S., Schaal, S.

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2016, IEEE, IEEE International Conference on Robotics and Automation, May 2016 (inproceedings)

Abstract
We consider the problem of model-based 3D- tracking of objects given dense depth images as input. Two difficulties preclude the application of a standard Gaussian filter to this problem. First of all, depth sensors are characterized by fat-tailed measurement noise. To address this issue, we show how a recently published robustification method for Gaussian filters can be applied to the problem at hand. Thereby, we avoid using heuristic outlier detection methods that simply reject measurements if they do not match the model. Secondly, the computational cost of the standard Gaussian filter is prohibitive due to the high-dimensional measurement, i.e. the depth image. To address this problem, we propose an approximation to reduce the computational complexity of the filter. In quantitative experiments on real data we show how our method clearly outperforms the standard Gaussian filter. Furthermore, we compare its performance to a particle-filter-based tracking method, and observe comparable computational efficiency and improved accuracy and smoothness of the estimates.

am ics

Video Bayesian Object Tracking Library Bayesian Filtering Framework Object Tracking Dataset link (url) DOI Project Page [BibTex]

Video Bayesian Object Tracking Library Bayesian Filtering Framework Object Tracking Dataset link (url) DOI Project Page [BibTex]


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Communication Rate Analysis for Event-based State Estimation

(Best student paper finalist)

Ebner, S., Trimpe, S.

In Proceedings of the 13th International Workshop on Discrete Event Systems, May 2016 (inproceedings)

am ics

PDF DOI [BibTex]

PDF DOI [BibTex]


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Robust calibration marker detection in powder bed images from laser beam melting processes

zur Jacobsmühlen, J., Achterhold, J., Kleszczynski, S., Witt, G., Merhof, D.

In 2016 IEEE International Conference on Industrial Technology (ICIT), pages: 910-915, March 2016 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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On designing an active tail for body-pitch control in legged robots via decoupling of control objectives

Heim, S. W., Ajallooeian, M., Eckert, P., Vespignani, M., Ijspeert, A.

In ASSISTIVE ROBOTICS: Proceedings of the 18th International Conference on CLAWAR 2015, pages: 256-264, 2016 (inproceedings)

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[BibTex]

[BibTex]


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Direct Visual-Inertial Odometry with Stereo Cameras

Usenko, V., Engel, J., Stueckler, J., Cremers, D.

In IEEE International Conference on Robotics and Automation (ICRA), 2016 (inproceedings)

ev

[BibTex]

[BibTex]


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CPA-SLAM: Consistent Plane-Model Alignment for Direct RGB-D SLAM

Ma, L., Kerl, C., Stueckler, J., Cremers, D.

In IEEE International Conference on Robotics and Automation (ICRA), 2016 (inproceedings)

ev

[BibTex]

[BibTex]


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Unsupervised Learning of Shape-Motion Patterns for Objects in Urban Street Scenes

Klostermann, D., Osep, A., Stueckler, J., Leibe, B.

In British Machine Vision Conference (BMVC), 2016 (inproceedings)

ev

[BibTex]

[BibTex]


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Scene Flow Propagation for Semantic Mapping and Object Discovery in Dynamic Street Scenes

Kochanov, D., Osep, A., Stueckler, J., Leibe, B.

In IEEE/RSJ Int. Conference on Intelligent Robots and Systems, IROS, 2016 (inproceedings)

ev

[BibTex]

[BibTex]


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Joint Object Pose Estimation and Shape Reconstruction in Urban Street Scenes Using 3D Shape Priors

Engelmann, F., Stueckler, J., Leibe, B.

In Proc. of the German Conference on Pattern Recognition (GCPR), 2016 (inproceedings)

ev

[BibTex]

[BibTex]

2007


An easy to use bluetooth scatternet protocol for fast data exchange in wireless sensor networks and autonomous robots
An easy to use bluetooth scatternet protocol for fast data exchange in wireless sensor networks and autonomous robots

Mockel, R., Spröwitz, A., Maye, J., Ijspeert, A. J.

In Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, pages: 2801-2806, IEEE, San Diego, CA, 2007 (inproceedings)

Abstract
We present a Bluetooth scatternet protocol (SNP) that provides the user with a serial link to all connected members in a transparent wireless Bluetooth network. By using only local decision making we can reduce the overhead of our scatternet protocol dramatically. We show how our SNP software layer simplifies a variety of tasks like the synchronization of central pattern generator controllers for actuators, collecting sensory data and building modular robot structures. The whole Bluetooth software stack including our new scatternet layer is implemented on a single Bluetooth and memory chip. To verify and characterize the SNP we provide data from experiments using real hardware instead of software simulation. This gives a realistic overview of the scatternet performance showing higher order effects that are difficult to be simulated correctly and guaranties the correct function of the SNP in real world applications.

dlg

DOI [BibTex]

2007


DOI [BibTex]


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Less Conservative Polytopic LPV Models for Charge Control by Combining Parameter Set Mapping and Set Intersection

Kwiatkowski, A., Trimpe, S., Werner, H.

In Proceedings of the 46th IEEE Conference on Decision and Control, 2007 (inproceedings)

am ics

DOI [BibTex]

DOI [BibTex]


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Hierarchical reactive control for a team of humanoid soccer robots

Behnke, S., Stueckler, J., Schreiber, M., Schulz, H., Böhnert, M., Meier, K.

In Proc. of the IEEE-RAS Int. Conf. on Humanoid Robots (Humanoids), pages: 622-629, November 2007 (inproceedings)

ev

link (url) DOI [BibTex]

link (url) DOI [BibTex]

2005


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Magnetization reversal behavior of nanogranular CoCrPt alloy thin films studied with magnetic transmission X-ray microscopy

Fischer, P., Im, M., Eimüller, T., Schütz, G., Shin, S.

In 286, pages: 311-314, Boulder, CO, USA, 2005 (inproceedings)

mms

[BibTex]

2005


[BibTex]


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Defects distribution of Pr2Fe14B hard magnetic magnet from amorphous to nanostructures characterized by positron annihilation spectroscopy

Wu, Y. C., Sprengel, W., Reimann, K., Reichle, K. J., Goll, D., Würschum, R., Schaefer, H. E.

In PRICM 5. Proceedings of the Fifth Pacific RIM International Conference on Advanced Materials and Processing, 475-479, pages: 2123-2126, Materials Science Forum, Trans Tech, Beijing, China, 2005 (inproceedings)

mms

[BibTex]

[BibTex]


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Implementing sub-ns time resolution into magnetic X-ray microscopies

Puzic, A., Stoll, H., Fischer, P., Van Waeyenberge, B., Raabe, J., Denbeaux, G., Haug, T., Weiss, D., Schütz, G.

In T115, pages: 1029-1031, Malmö/Lund, Sweden, 2005 (inproceedings)

mms

[BibTex]

[BibTex]