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2015


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Towards Optimal Robot Navigation in Urban Homes

Ventura, R., Ahmad, A.

In RoboCup 2014: Robot World Cup XVIII, pages: 318-331, Lecture Notes in Computer Science ; 8992, Springer, Cham, Switzerland, 18th Annual RoboCup International Symposium, 2015 (inproceedings)

Abstract
The work presented in this paper is motivated by the goal of dependable autonomous navigation of mobile robots. This goal is a fundamental requirement for having autonomous robots in spaces such as domestic spaces and public establishments, left unattended by technical staff. In this paper we tackle this problem by taking an optimization approach: on one hand, we use a Fast Marching Approach for path planning, resulting in optimal paths in the absence of unmapped obstacles, and on the other hand we use a Dynamic Window Approach for guidance. To the best of our knowledge, the combination of these two methods is novel. We evaluate the approach on a real mobile robot, capable of moving at high speed. The evaluation makes use of an external ground truth system. We report controlled experiments that we performed, including the presence of people moving randomly nearby the robot. In our long term experiments we report a total distance of 18 km traveled during 11 hours of movement time.

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DOI [BibTex]

2015


DOI [BibTex]


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Neural Adaptive Sequential Monte Carlo

Gu, S., Ghahramani, Z., Turner, R. E.

Advances in Neural Information Processing Systems 28, pages: 2629-2637, (Editors: Corinna Cortes, Neil D. Lawrence, Daniel D. Lee, Masashi Sugiyama, and Roman Garnett), 29th Annual Conference on Neural Information Processing Systems (NIPS), 2015 (conference)

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PDF Supplementary [BibTex]

PDF Supplementary [BibTex]


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Discovering Temporal Causal Relations from Subsampled Data

Gong, M., Zhang, K., Schölkopf, B., Tao, D., Geiger, P.

In Proceedings of the 32nd International Conference on Machine Learning, 37, pages: 1898–1906, JMLR Workshop and Conference Proceedings, (Editors: F. Bach and D. Blei), JMLR, ICML, 2015 (inproceedings)

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PDF link (url) [BibTex]

PDF link (url) [BibTex]


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Active Nearest Neighbors in Changing Environments

Berlind, C., Urner, R.

In Proceedings of the 32nd International Conference on Machine Learning, 37, pages: 1870-1879, JMLR Workshop and Conference Proceedings, (Editors: Bach, F. and Blei, D. ), JMLR, ICML, 2015 (inproceedings)

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link (url) [BibTex]

link (url) [BibTex]


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Learning Inverse Dynamics Models with Contacts

Calandra, R., Ivaldi, S., Deisenroth, M., Rückert, E., Peters, J.

In IEEE International Conference on Robotics and Automation, pages: 3186-3191, ICRA, 2015 (inproceedings)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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A Probabilistic Framework for Semi-Autonomous Robots Based on Interaction Primitives with Phase Estimation

Maeda, G., Neumann, G., Ewerton, M., Lioutikov, R., Peters, J.

In Proceedings of the International Symposium of Robotics Research, ISRR, 2015 (inproceedings)

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link (url) [BibTex]

link (url) [BibTex]


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Real-Time Object Detection, Localization and Verification for Fast Robotic Depalletizing

Holz, D., Topalidou-Kyniazopoulou, A., Stueckler, J., Behnke, S.

In IEEE International Conference on Intelligent Robots and Systems (IROS), 2015 (inproceedings)

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link (url) [BibTex]

link (url) [BibTex]


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Dense Continuous-Time Tracking and Mapping with Rolling Shutter RGB-D Cameras

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

In IEEE International Conference on Computer Vision (ICCV), Santiago, Chile, 2015, {[video][supplementary][datasets]} (inproceedings)

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[BibTex]

[BibTex]


Thumb xl 2016 peer grading
Peer grading in a course on algorithms and data structures

Sajjadi, M. S. M., Alamgir, M., von Luxburg, U.

Workshop on Machine Learning for Education (ML4Ed) at the 32th International Conference on Machine Learning (ICML), 2015 (conference)

ei

Arxiv [BibTex]

Arxiv [BibTex]


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Joint 3D Object and Layout Inference from a single RGB-D Image

(Best Paper Award)

Geiger, A., Wang, C.

In German Conference on Pattern Recognition (GCPR), 9358, pages: 183-195, Lecture Notes in Computer Science, Springer International Publishing, 2015 (inproceedings)

Abstract
Inferring 3D objects and the layout of indoor scenes from a single RGB-D image captured with a Kinect camera is a challenging task. Towards this goal, we propose a high-order graphical model and jointly reason about the layout, objects and superpixels in the image. In contrast to existing holistic approaches, our model leverages detailed 3D geometry using inverse graphics and explicitly enforces occlusion and visibility constraints for respecting scene properties and projective geometry. We cast the task as MAP inference in a factor graph and solve it efficiently using message passing. We evaluate our method with respect to several baselines on the challenging NYUv2 indoor dataset using 21 object categories. Our experiments demonstrate that the proposed method is able to infer scenes with a large degree of clutter and occlusions.

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pdf suppmat video project DOI [BibTex]

pdf suppmat video project DOI [BibTex]


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Removing systematic errors for exoplanet search via latent causes

Schölkopf, B., Hogg, D., Wang, D., Foreman-Mackey, D., Janzing, D., Simon-Gabriel, C. J., Peters, J.

In Proceedings of The 32nd International Conference on Machine Learning, 37, pages: 2218–2226, JMLR Workshop and Conference Proceedings, (Editors: Bach, F. and Blei, D.), JMLR, ICML, 2015 (inproceedings)

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Extended version on arXiv link (url) [BibTex]

Extended version on arXiv link (url) [BibTex]


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Causal Inference by Identification of Vector Autoregressive Processes with Hidden Components

Geiger, P., Zhang, K., Schölkopf, B., Gong, M., Janzing, D.

In Proceedings of the 32nd International Conference on Machine Learning, 37, pages: 1917–1925, JMLR Workshop and Conference Proceedings, (Editors: F. Bach and D. Blei), JMLR, ICML, 2015 (inproceedings)

ei

PDF link (url) [BibTex]

PDF link (url) [BibTex]


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Brain-Computer Interfacing in Amyotrophic Lateral Sclerosis: Implications of a Resting-State EEG Analysis

Jayaram, V., Widmann, N., Förster, C., Fomina, T., Hohmann, M. R., Müller vom Hagen, J., Synofzik, M., Schölkopf, B., Schöls, L., Grosse-Wentrup, M.

In Proceedings of the 37th IEEE Conference for Engineering in Medicine and Biology, pages: 6979-6982, EMBC, 2015 (inproceedings)

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Identification of the Default Mode Network with Electroencephalography

Fomina, T., Hohmann, M. R., Schölkopf, B., Grosse-Wentrup, M.

In Proceedings of the 37th IEEE Conference for Engineering in Medicine and Biology, pages: 7566-7569, EMBC, 2015 (inproceedings)

ei

DOI [BibTex]

DOI [BibTex]


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Towards Cognitive Brain-Computer Interfaces for Patients with Amyotrophic Lateral Sclerosis

Fomina, T., Schölkopf, B., Grosse-Wentrup, M.

In 7th Computer Science and Electronic Engineering Conference, pages: 77-80, Curran Associates, Inc., CEEC, 2015 (inproceedings)

ei

DOI [BibTex]

DOI [BibTex]


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Towards Learning Hierarchical Skills for Multi-Phase Manipulation Tasks

Kroemer, O., Daniel, C., Neumann, G., van Hoof, H., Peters, J.

In IEEE International Conference on Robotics and Automation, pages: 1503 - 1510, ICRA, 2015 (inproceedings)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Probabilistic Line Searches for Stochastic Optimization

Mahsereci, M., Hennig, P.

In Advances in Neural Information Processing Systems 28, pages: 181-189, (Editors: C. Cortes, N.D. Lawrence, D.D. Lee, M. Sugiyama and R. Garnett), Curran Associates, Inc., 29th Annual Conference on Neural Information Processing Systems (NIPS), 2015 (inproceedings)

Abstract
In deterministic optimization, line searches are a standard tool ensuring stability and efficiency. Where only stochastic gradients are available, no direct equivalent has so far been formulated, because uncertain gradients do not allow for a strict sequence of decisions collapsing the search space. We construct a probabilistic line search by combining the structure of existing deterministic methods with notions from Bayesian optimization. Our method retains a Gaussian process surrogate of the univariate optimization objective, and uses a probabilistic belief over the Wolfe conditions to monitor the descent. The algorithm has very low computational cost, and no user-controlled parameters. Experiments show that it effectively removes the need to define a learning rate for stochastic gradient descent. [You can find the matlab research code under `attachments' below. The zip-file contains a minimal working example. The docstring in probLineSearch.m contains additional information. A more polished implementation in C++ will be published here at a later point. For comments and questions about the code please write to mmahsereci@tue.mpg.de.]

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Matlab research code link (url) [BibTex]

Matlab research code link (url) [BibTex]


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Force estimation and slip detection/classification for grip control using a biomimetic tactile sensor

Su, Z., Hausman, K., Chebotar, Y., Molchanov, A., Loeb, G. E., Sukhatme, G. S., Schaal, S.

In IEEE-RAS International Conference on Humanoid Robots (Humanoids), pages: 297-303, 2015 (inproceedings)

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link (url) [BibTex]

link (url) [BibTex]


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BACKSHIFT: Learning causal cyclic graphs from unknown shift interventions

Rothenhäusler, D., Heinze, C., Peters, J., Meinshausen, N.

Advances in Neural Information Processing Systems 28, pages: 1513-1521, (Editors: C. Cortes, N.D. Lawrence, D.D. Lee, M. Sugiyama and R. Garnett), Curran Associates, Inc., 29th Annual Conference on Neural Information Processing Systems (NIPS), 2015 (conference)

ei

link (url) [BibTex]

link (url) [BibTex]


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Particle Gibbs for Infinite Hidden Markov Models

Tripuraneni*, N., Gu*, S., Ge, H., Ghahramani, Z.

Advances in Neural Information Processing Systems 28, pages: 2395-2403, (Editors: Corinna Cortes, Neil D. Lawrence, Daniel D. Lee, Masashi Sugiyama, and Roman Garnett), 29th Annual Conference on Neural Information Processing Systems (NIPS), 2015, *equal contribution (conference)

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PDF [BibTex]

PDF [BibTex]


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Large-Scale Direct SLAM with Stereo Cameras

Engel, J., Stueckler, J., Cremers, D.

In IEEE International Conference on Intelligent Robots and Systems (IROS), 2015 (inproceedings)

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[BibTex]

[BibTex]


Thumb xl 2016 peer grading
Peer grading in a course on algorithms and data structures

Sajjadi, M. S. M., Alamgir, M., von Luxburg, U.

Workshop on Crowdsourcing and Machine Learning (CrowdML) Workshop on Machine Learning for Education (ML4Ed) at at the 32th International Conference on Machine Learning (ICML), 2015 (conference)

ei

Arxiv [BibTex]

Arxiv [BibTex]


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Regressive virtual metric learning

Perrot, M., Habrard, A.

In Proceedings Neural Information Processing Systems, Neural Information Processing Systems (NIPS), 2015 (inproceedings)

[BibTex]

[BibTex]


Thumb xl screen shot 2015 05 07 at 11.56.54
3D Object Class Detection in the Wild

Pepik, B., Stark, M., Gehler, P., Ritschel, T., Schiele, B.

In Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), IEEE, Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2015 (inproceedings)

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Project Page [BibTex]

Project Page [BibTex]


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Discrete Optimization for Optical Flow

Menze, M., Heipke, C., Geiger, A.

In German Conference on Pattern Recognition (GCPR), 9358, pages: 16-28, Springer International Publishing, 2015 (inproceedings)

Abstract
We propose to look at large-displacement optical flow from a discrete point of view. Motivated by the observation that sub-pixel accuracy is easily obtained given pixel-accurate optical flow, we conjecture that computing the integral part is the hardest piece of the problem. Consequently, we formulate optical flow estimation as a discrete inference problem in a conditional random field, followed by sub-pixel refinement. Naive discretization of the 2D flow space, however, is intractable due to the resulting size of the label set. In this paper, we therefore investigate three different strategies, each able to reduce computation and memory demands by several orders of magnitude. Their combination allows us to estimate large-displacement optical flow both accurately and efficiently and demonstrates the potential of discrete optimization for optical flow. We obtain state-of-the-art performance on MPI Sintel and KITTI.

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pdf suppmat project DOI [BibTex]

pdf suppmat project DOI [BibTex]


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A Random Riemannian Metric for Probabilistic Shortest-Path Tractography

Hauberg, S., Schober, M., Liptrot, M., Hennig, P., Feragen, A.

In 18th International Conference on Medical Image Computing and Computer Assisted Intervention, 9349, pages: 597-604, Lecture Notes in Computer Science, MICCAI, 2015 (inproceedings)

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PDF DOI [BibTex]

PDF DOI [BibTex]


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Recent Methodological Advances in Causal Discovery and Inference

Spirtes, P., Zhang, K.

In 15th Conference on Theoretical Aspects of Rationality and Knowledge, pages: 23-35, (Editors: Ramanujam, R.), TARK, 2015 (inproceedings)

ei

[BibTex]

[BibTex]


Thumb xl screen shot 2015 08 22 at 22.13.35
Policy Learning with Hypothesis Based Local Action Selection

Sankaran, B., Bohg, J., Ratliff, N., Schaal, S.

In Reinforcement Learning and Decision Making, 2015 (inproceedings)

Abstract
For robots to be able to manipulate in unknown and unstructured environments the robot should be capable of operating under partial observability of the environment. Object occlusions and unmodeled environments are some of the factors that result in partial observability. A common scenario where this is encountered is manipulation in clutter. In the case that the robot needs to locate an object of interest and manipulate it, it needs to perform a series of decluttering actions to accurately detect the object of interest. To perform such a series of actions, the robot also needs to account for the dynamics of objects in the environment and how they react to contact. This is a non trivial problem since one needs to reason not only about robot-object interactions but also object-object interactions in the presence of contact. In the example scenario of manipulation in clutter, the state vector would have to account for the pose of the object of interest and the structure of the surrounding environment. The process model would have to account for all the aforementioned robot-object, object-object interactions. The complexity of the process model grows exponentially as the number of objects in the scene increases. This is commonly the case in unstructured environments. Hence it is not reasonable to attempt to model all object-object and robot-object interactions explicitly. Under this setting we propose a hypothesis based action selection algorithm where we construct a hypothesis set of the possible poses of an object of interest given the current evidence in the scene and select actions based on our current set of hypothesis. This hypothesis set tends to represent the belief about the structure of the environment and the number of poses the object of interest can take. The agent's only stopping criterion is when the uncertainty regarding the pose of the object is fully resolved.

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Web Project Page [BibTex]


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Joint 3D Estimation of Vehicles and Scene Flow

Menze, M., Heipke, C., Geiger, A.

In Proc. of the ISPRS Workshop on Image Sequence Analysis (ISA), 2015 (inproceedings)

Abstract
Three-dimensional reconstruction of dynamic scenes is an important prerequisite for applications like mobile robotics or autonomous driving. While much progress has been made in recent years, imaging conditions in natural outdoor environments are still very challenging for current reconstruction and recognition methods. In this paper, we propose a novel unified approach which reasons jointly about 3D scene flow as well as the pose, shape and motion of vehicles in the scene. Towards this goal, we incorporate a deformable CAD model into a slanted-plane conditional random field for scene flow estimation and enforce shape consistency between the rendered 3D models and the parameters of all superpixels in the image. The association of superpixels to objects is established by an index variable which implicitly enables model selection. We evaluate our approach on the challenging KITTI scene flow dataset in terms of object and scene flow estimation. Our results provide a prove of concept and demonstrate the usefulness of our method.

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PDF [BibTex]

PDF [BibTex]


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Learning Optimal Striking Points for A Ping-Pong Playing Robot

Huang, Y., Schölkopf, B., Peters, J.

In IEEE/RSJ International Conference on Intelligent Robots and Systems, pages: 4587-4592, IROS, 2015 (inproceedings)

am ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Model-Based Relative Entropy Stochastic Search

Abdolmaleki, A., Peters, J., Neumann, G.

In Advances in Neural Information Processing Systems 28, pages: 3523-3531, (Editors: C. Cortes, N.D. Lawrence, D.D. Lee, M. Sugiyama and R. Garnett), Curran Associates, Inc., 29th Annual Conference on Neural Information Processing Systems (NIPS), 2015 (inproceedings)

am ei

link (url) [BibTex]

link (url) [BibTex]


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Modeling Spatio-Temporal Variability in Human-Robot Interaction with Probabilistic Movement Primitives

Ewerton, M., Neumann, G., Lioutikov, R., Ben Amor, H., Peters, J., Maeda, G.

In Workshop on Machine Learning for Social Robotics, ICRA, 2015 (inproceedings)

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link (url) [BibTex]

link (url) [BibTex]


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Extracting Low-Dimensional Control Variables for Movement Primitives

Rueckert, E., Mundo, J., Paraschos, A., Peters, J., Neumann, G.

In IEEE International Conference on Robotics and Automation, pages: 1511-1518, ICRA, 2015 (inproceedings)

am ei

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Self-calibration of optical lenses

Hirsch, M., Schölkopf, B.

In IEEE International Conference on Computer Vision (ICCV 2015), pages: 612-620, IEEE, 2015 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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A Setup for multi-UAV hardware-in-the-loop simulations

Odelga, M., Stegagno, P., Bülthoff, H., Ahmad, A.

In pages: 204-210, IEEE, 3rd Workshop on Research, Education and Development of Unmanned Aerial Systems (RED-UAS), 2015 (inproceedings)

Abstract
In this paper, we present a hardware in the loop simulation setup for multi-UAV systems. With our setup, we are able to command the robots simulated in Gazebo, a popular open source ROS-enabled physical simulator, using the computational units that are embedded on our quadrotor UAVs. Hence, we can test in simulation not only the correct execution of algorithms, but also the computational feasibility directly on the robot hardware. In addition, since our setup is inherently multi-robot, we can also test the communication flow among the robots. We provide two use cases to show the characteristics of our setup.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


Thumb xl screen shot 2018 02 03 at 7.49.07 pm
Comparing the effect of different spine and leg designs for a small bounding quadruped robot

Eckert, P., Spröwitz, A., Witte, H., Ijspeert, A. J.

In Proceedings of ICRA, pages: 3128-3133, Seattle, Washington, USA, 2015 (inproceedings)

Abstract
We present Lynx-robot, a quadruped, modular, compliant machine. It alternately features a directly actuated, single-joint spine design, or an actively supported, passive compliant, multi-joint spine configuration. Both spine con- figurations bend in the sagittal plane. This study aims at characterizing these two, largely different spine concepts, for a bounding gait of a robot with a three segmented, pantograph leg design. An earlier, similar-sized, bounding, quadruped robot named Bobcat with a two-segment leg design and a directly actuated, single-joint spine design serves as a comparison robot, to study and compare the effect of the leg design on speed, while keeping the spine design fixed. Both proposed spine designs (single rotatory and active and multi-joint compliant) reach moderate, self-stable speeds.

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link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


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Smooth Loops from Unconstrained Video

Sevilla-Lara, L., Wulff, J., Sunkavalli, K., Shechtman, E.

In Computer Graphics Forum (Proceedings of EGSR), 34(4):99-107, Eurographics Symposium on Rendering, 2015 (inproceedings)

Abstract
Converting unconstrained video sequences into videos that loop seamlessly is an extremely challenging problem. In this work, we take the first steps towards automating this process by focusing on an important subclass of videos containing a single dominant foreground object. Our technique makes two novel contributions over previous work: first, we propose a correspondence-based similarity metric to automatically identify a good transition point in the video where the appearance and dynamics of the foreground are most consistent. Second, we develop a technique that aligns both the foreground and background about this transition point using a combination of global camera path planning and patch-based video morphing. We demonstrate that this allows us to create natural, compelling, loopy videos from a wide range of videos collected from the internet.

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pdf link (url) DOI Project Page [BibTex]

pdf link (url) DOI Project Page [BibTex]


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Telling cause from effect in deterministic linear dynamical systems

Shajarisales, N., Janzing, D., Schölkopf, B., Besserve, M.

In Proceedings of the 32nd International Conference on Machine Learning, 37, pages: 285–294, JMLR Workshop and Conference Proceedings, (Editors: F. Bach and D. Blei), JMLR, ICML, 2015 (inproceedings)

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PDF [BibTex]

PDF [BibTex]


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A New Perspective and Extension of the Gaussian Filter

Wüthrich, M., Trimpe, S., Kappler, D., Schaal, S.

In Robotics: Science and Systems, 2015 (inproceedings)

Abstract
The Gaussian Filter (GF) is one of the most widely used filtering algorithms; instances are the Extended Kalman Filter, the Unscented Kalman Filter and the Divided Difference Filter. GFs represent the belief of the current state by a Gaussian with the mean being an affine function of the measurement. We show that this representation can be too restrictive to accurately capture the dependencies in systems with nonlinear observation models, and we investigate how the GF can be generalized to alleviate this problem. To this end we view the GF from a variational-inference perspective, and analyze how restrictions on the form of the belief can be relaxed while maintaining simplicity and efficiency. This analysis provides a basis for generalizations of the GF. We propose one such generalization which coincides with a GF using a virtual measurement, obtained by applying a nonlinear function to the actual measurement. Numerical experiments show that the proposed Feature Gaussian Filter (FGF) can have a substantial performance advantage over the standard GF for systems with nonlinear observation models.

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Web PDF Project Page [BibTex]


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A Cognitive Brain-Computer Interface for Patients with Amyotrophic Lateral Sclerosis

Hohmann, M. R., Fomina, T., Jayaram, V., Widmann, N., Förster, C., Müller vom Hagen, J., Synofzik, M., Schölkopf, B., Schöls, L., Grosse-Wentrup, M.

In Proceedings of the 2015 IEEE International Conference on Systems, Man, and Cybernetics, pages: 3187-3191, SMC, 2015 (inproceedings)

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Predicting Human Reaching Motion in Collaborative Tasks Using Inverse Optimal Control and Iterative Re-planning

Jim Mainprice, Rafi Hayne, Dmitry Berenson

In 2015 (inproceedings)

Abstract
To enable safe and efficient human-robot collaboration in shared workspaces, it is important for the robot to predict how a human will move when performing a task. While predicting human motion for tasks not known a priori is very challenging, we argue that single-arm reaching motions for known tasks in collaborative settings (which are especially relevant for manufacturing) are indeed predictable. Two hypotheses underlie our approach for predicting such motions: First, that the trajectory the human performs is optimal with respect to an unknown cost function, and second, that human adaptation to their partner’s motion can be captured well through iterative replanning with the above cost function. The key to our approach is thus to learn a cost function which “explains” the motion of the human. To do this, we gather example trajectories from two participants performing a collaborative assembly task using motion capture. We then use Inverse Optimal Control to learn a cost function from these trajectories. Finally, we predict a human’s motion for a given task by iteratively re-planning a trajectory for a 23 DoFs human kinematic model using the STOMP algorithm with the learned cost function in the presence of a moving collaborator. Our results suggest that our method outperforms baseline methods and generalizes well for tasks similar to those that were demonstrated.

[BibTex]


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Efficient Learning of Linear Separators under Bounded Noise

Awasthi, P., Balcan, M., Haghtalab, N., Urner, R.

In Proceedings of the 28th Conference on Learning Theory, 40, pages: 167-190, (Editors: Grünwald, P. and Hazan, E. and Kale, S.), JMLR, COLT, 2015 (inproceedings)

ei

link (url) [BibTex]

link (url) [BibTex]


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Learning multiple collaborative tasks with a mixture of Interaction Primitives

Ewerton, M., Neumann, G., Lioutikov, R., Ben Amor, H., Peters, J., Maeda, G.

In IEEE International Conference on Robotics and Automation, pages: 1535-1542, ICRA, 2015 (inproceedings)

am ei

link (url) DOI [BibTex]

link (url) DOI [BibTex]


Thumb xl result overlayed
Onboard robust person detection and tracking for domestic service robots

Sanz, D., Ahmad, A., Lima, P.

In Robot 2015: Second Iberian Robotics Conference, pages: 547-559, Advances in Intelligent Systems and Computing ; 418, Springer, Cham, Switzerland, Second Iberian Robotics Conference (ROBOT'2015), 2015 (inproceedings)

Abstract
Domestic assistance for the elderly and impaired people is one of the biggest upcoming challenges of our society. Consequently, in-home care through domestic service robots is identified as one of the most important application area of robotics research. Assistive tasks may range from visitor reception at the door to catering for owner's small daily necessities within a house. Since most of these tasks require the robot to interact directly with humans, a predominant robot functionality is to detect and track humans in real time: either the owner of the robot or visitors at home or both. In this article we present a robust method for such a functionality that combines depth-based segmentation and visual detection. The robustness of our method lies in its capability to not only identify partially occluded humans (e.g., with only torso visible) but also to do so in varying lighting conditions. We thoroughly validate our method through extensive experiments on real robot datasets and comparisons with the ground truth. The datasets were collected on a home-like environment set up within the context of RoboCup@Home and RoCKIn@Home competitions.

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DOI [BibTex]

DOI [BibTex]


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Subspace Alignement based Domain Adaptation for RCNN detector

Raj, A., V., N., Tuytelaars, T.

Proceedings of the 26th British Machine Vision Conference (BMVC 2015), pages: 166.1-166.11, (Editors: Xianghua Xie and Mark W. Jones and Gary K. L. Tam), 2015 (conference)

ei

DOI [BibTex]

DOI [BibTex]


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Practical Probabilistic Programming with Monads

Ścibior, A., Ghahramani, Z., Gordon, A. D.

Proceedings of the 2015 ACM SIGPLAN Symposium on Haskell, pages: 165-176, Haskell ’15, ACM, 2015 (conference)

ei

DOI [BibTex]

DOI [BibTex]


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Whole-body motor strategies for balancing on a beam when changing the number of available degrees of freedom

Chiovetto, E, Huber, M, Righetti, L., Schaal, S., Sternad, D, Giese, M.

In Progress in Motor Control X, Budapest, Hungry, 2015 (inproceedings)

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[BibTex]

[BibTex]


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Motion Cooperation: Smooth Piece-Wise Rigid Scene Flow from RGB-D Images

Jaimez, M., Souiai, M., Stueckler, J., Gonzalez-Jimenez, J., Cremers, D.

In Proc. of the Int. Conference on 3D Vision (3DV), October 2015, {[video]} (inproceedings)

ev

[BibTex]

[BibTex]


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Learning from others: Adult and child strategies in assessing conflicting ratings

Hu, J., Lieder, F., Griffiths, T. L., Xu, F.

In Biennial Meeting of the Society for Research in Child Development, Philadelphia, Pennsylvania, USA, 2015 (inproceedings)

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[BibTex]

[BibTex]


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Combined FORC and x-ray microscopy study of magnetisation reversal in antidot lattices

Gräfe, J., Haering, F., Stahl, C., Weigand, M., Skripnik, M., Nowak, U., Ziemann, P., Wiedwald, U., Schütz, G., Goering, E.

In IEEE International Magnetics Conference (INTERMAG 2015), IEEE, Beijing, China, 2015 (inproceedings)

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DOI Project Page Project Page [BibTex]

DOI Project Page Project Page [BibTex]