Header logo is


2016


no image
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 Gaussian 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 - Automatic LQR Tuning Based on Gaussian Process Global Optimization - ICRA 2016 Video - Automatic Controller Tuning on a Two-legged Robot PDF DOI Project Page [BibTex]

Video - Automatic LQR Tuning Based on Gaussian Process Global Optimization - ICRA 2016 Video - Automatic Controller Tuning on a Two-legged Robot 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]


no image
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]


no image
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)

ev

DOI [BibTex]

DOI [BibTex]


no image
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]


no image
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]


no image
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]


no image
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]


no image
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]

2011


no image
An Experimental Demonstration of a Distributed and Event-based State Estimation Algorithm

(Best Interactive Paper Award (top out of 450))

Trimpe, S., D’Andrea, R.

In Proceedings of the 18th IFAC World Congress, 2011 (inproceedings)

am ics

PDF DOI [BibTex]

2011


PDF DOI [BibTex]


no image
Reduced Communication State Estimation for Control of an Unstable Networked Control System

Trimpe, S., D’Andrea, R.

In Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011 (inproceedings)

am ics

PDF Supplementary material DOI [BibTex]

PDF Supplementary material DOI [BibTex]


no image
Following human guidance to cooperatively carry a large object

Stueckler, J., Behnke, S.

In Proc. of the 11th IEEE-RAS Int. Conf. on Humanoid Robots (Humanoids), pages: 218-223, October 2011 (inproceedings)

ev

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
Real-Time 3D Perception and Efficient Grasp Planning for Everyday Manipulation Tasks.

Stueckler, J., Steffens, R., Holz, D., Behnke, S.

In Proc. of the European Conf. on Mobile Robots (ECMR), pages: 177-182, 2011 (inproceedings)

ev

link (url) [BibTex]

link (url) [BibTex]


no image
Towards joint attention for a domestic service robot - person awareness and gesture recognition using Time-of-Flight cameras

Droeschel, D., Stueckler, J., Holz, D., Behnke, S.

In Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA), pages: 1205-1210, May 2011 (inproceedings)

ev

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
Compliant Task-Space Control with Back-Drivable Servo Actuators

Stueckler, J., Behnke, S.

In RoboCup, 7416, pages: 78-89, Lecture Notes in Computer Science, Springer, 2011 (inproceedings)

ev

link (url) [BibTex]

link (url) [BibTex]


no image
Interest point detection in depth images through scale-space surface analysis

Stueckler, J., Behnke, S.

In Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA), pages: 3568-3574, May 2011 (inproceedings)

ev

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
Learning to Interpret Pointing Gestures with a Time-of-flight Camera

Droeschel, D., Stueckler, J., Behnke, S.

In Proceedings of the 6th International Conference on Human-robot Interaction, pages: 481-488, ACM, 2011 (inproceedings)

ev

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
Efficient Multi-resolution Plane Segmentation of 3D Point Clouds

Oehler, B., Stueckler, J., Welle, J., Schulz, D., Behnke, S.

In Proc. of the Int. Conf. on Intelligent Robotics and Applications (ICIRA), 7102, pages: 145-156, Lecture Notes in Computer Science, Springer Berlin Heidelberg, 2011 (inproceedings)

ev

link (url) DOI [BibTex]

link (url) DOI [BibTex]

2009


no image
A Limiting Property of the Matrix Exponential with Application to Multi-loop Control

Trimpe, S., D’Andrea, R.

In Proceedings of the Joint 48th IEEE Conference on Decision (CDC) and Control and 28th Chinese Control Conference, 2009 (inproceedings)

am ics

PDF DOI [BibTex]

2009


PDF DOI [BibTex]


no image
Integrating indoor mobility, object manipulation, and intuitive interaction for domestic service tasks

Stueckler, J., Behnke, S.

In Proc. of the IEEE-RAS Int. Conf. on Humanoid Robots (Humanoids), pages: 506-513, December 2009 (inproceedings)

ev

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
Dynamaid, an Anthropomorphic Robot for Research on Domestic Service Applications

Stueckler, J., Schreiber, M., Behnke, S.

In Proc. of the European Conference on Mobile Robots (ECMR), pages: 87-92, 2009 (inproceedings)

ev

link (url) [BibTex]

link (url) [BibTex]