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2015


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Perception of Deformable Objects and Compliant Manipulation for Service Robots

Stueckler, J., Behnke, S.

In Soft Robotics: From Theory to Applications, Springer, 2015 (inbook)

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link (url) [BibTex]

2015


link (url) [BibTex]

2014


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Active Recognition and Manipulation for Mobile Robot Bin Picking

Holz, D., Nieuwenhuisen, M., Droeschel, D., Stueckler, J., Berner, A., Li, J., Klein, R., Behnke, S.

In Gearing Up and Accelerating Cross-fertilization between Academic and Industrial Robotics Research in Europe: Technology Transfer Experiments from the ECHORD Project, pages: 133-153, Springer, 2014 (inbook)

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link (url) DOI [BibTex]

2014


link (url) DOI [BibTex]


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Increasing Flexibility of Mobile Manipulation and Intuitive Human-Robot Interaction in RoboCup@Home

Stueckler, J., Droeschel, D., Gräve, K., Holz, D., Schreiber, M., Topaldou-Kyniazopoulou, A., Schwarz, M., Behnke, S.

In RoboCup 2013, Robot Soccer World Cup XVII, pages: 135-146, Springer, 2014 (inbook)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Efficient Dense Registration, Segmentation, and Modeling Methods for RGB-D Environment Perception

Stueckler, J.

Faculty of Mathematics and Natural Sciences, University of Bonn, Germany, 2014 (phdthesis)

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link (url) [BibTex]

link (url) [BibTex]

2013


Probabilistic Models for 3D Urban Scene Understanding from Movable Platforms
Probabilistic Models for 3D Urban Scene Understanding from Movable Platforms

Geiger, A.

Karlsruhe Institute of Technology, Karlsruhe Institute of Technology, April 2013 (phdthesis)

Abstract
Visual 3D scene understanding is an important component in autonomous driving and robot navigation. Intelligent vehicles for example often base their decisions on observations obtained from video cameras as they are cheap and easy to employ. Inner-city intersections represent an interesting but also very challenging scenario in this context: The road layout may be very complex and observations are often noisy or even missing due to heavy occlusions. While Highway navigation and autonomous driving on simple and annotated intersections have already been demonstrated successfully, understanding and navigating general inner-city crossings with little prior knowledge remains an unsolved problem. This thesis is a contribution to understanding multi-object traffic scenes from video sequences. All data is provided by a camera system which is mounted on top of the autonomous driving platform AnnieWAY. The proposed probabilistic generative model reasons jointly about the 3D scene layout as well as the 3D location and orientation of objects in the scene. In particular, the scene topology, geometry as well as traffic activities are inferred from short video sequences. The model takes advantage of monocular information in the form of vehicle tracklets, vanishing lines and semantic labels. Additionally, the benefit of stereo features such as 3D scene flow and occupancy grids is investigated. Motivated by the impressive driving capabilities of humans, no further information such as GPS, lidar, radar or map knowledge is required. Experiments conducted on 113 representative intersection sequences show that the developed approach successfully infers the correct layout in a variety of difficult scenarios. To evaluate the importance of each feature cue, experiments with different feature combinations are conducted. Additionally, the proposed method is shown to improve object detection and object orientation estimation performance.

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pdf [BibTex]

2013


pdf [BibTex]


Motor Control Adaptation to Changes in Robot Body Dynamics for a Compliant Quadruped Robot
Motor Control Adaptation to Changes in Robot Body Dynamics for a Compliant Quadruped Robot

Pouya, S., Eckert, P., Spröwitz, A., Moc̈kel, R., Ijspeert, A. J.

In Biomimetic and Biohybrid Systems, 8064, pages: 434-437, Lecture Notes in Computer Science, Springer, Heidelberg, 2013 (incollection)

Abstract
One of the major deficiencies of current robots in comparison to living beings is the ability to adapt to new conditions either resulting from environmental changes or their own dynamics. In this work we focus on situations where the robot experiences involuntary changes in its body particularly in its limbs’ inertia. Inspired from its biological counterparts we are interested in enabling the robot to adapt its motor control to the new system dynamics. To reach this goal, we propose two different control strategies and compare their performance when handling these modifications. Our results show substantial improvements in adaptivity to body changes when the robot is aware of its new dynamics and can exploit this knowledge in synthesising new motor control.

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DOI [BibTex]

DOI [BibTex]


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NimbRo@Home: Winning Team of the RoboCup@Home Competition 2012

Stueckler, J., Badami, I., Droeschel, D., Gräve, K., Holz, D., McElhone, M., Nieuwenhuisen, M., Schreiber, M., Schwarz, M., Behnke, S.

In RoboCup 2012, Robot Soccer World Cup XVI, pages: 94-105, Springer, 2013 (inbook)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]

2012


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Towards Robust Mobility, Flexible Object Manipulation, and Intuitive Multimodal Interaction for Domestic Service Robots

Stueckler, J., Droeschel, D., Gräve, K., Holz, D., Kläß, J., Schreiber, M., Steffens, R., Behnke, S.

In RoboCup 2011, Robot Soccer World Cup XV, pages: 51-62, Springer, 2012 (inbook)

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link (url) DOI [BibTex]

2012


link (url) DOI [BibTex]