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2015


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Learning Torque Control in Presence of Contacts using Tactile Sensing from Robot Skin

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

In 15th IEEE-RAS International Conference on Humanoid Robots, pages: 690-695, Humanoids, November 2015 (inproceedings)

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link (url) DOI [BibTex]

2015


link (url) DOI [BibTex]


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Evaluation of Interactive Object Recognition with Tactile Sensing

Hoelscher, J., Peters, J., Hermans, T.

In 15th IEEE-RAS International Conference on Humanoid Robots, pages: 310-317, Humanoids, November 2015 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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Optimizing Robot Striking Movement Primitives with Iterative Learning Control

Koc, O., Maeda, G., Neumann, G., Peters, J.

In 15th IEEE-RAS International Conference on Humanoid Robots, pages: 80-87, Humanoids, November 2015 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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A Comparison of Contact Distribution Representations for Learning to Predict Object Interactions

Leischnig, S., Luettgen, S., Kroemer, O., Peters, J.

In 15th IEEE-RAS International Conference on Humanoid Robots, pages: 616-622, Humanoids, November 2015 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


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First-Person Tele-Operation of a Humanoid Robot

Fritsche, L., Unverzagt, F., Peters, J., Calandra, R.

In 15th IEEE-RAS International Conference on Humanoid Robots, pages: 997-1002, Humanoids, November 2015 (inproceedings)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Probabilistic Segmentation Applied to an Assembly Task

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

In 15th IEEE-RAS International Conference on Humanoid Robots, pages: 533-540, Humanoids, November 2015 (inproceedings)

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DOI [BibTex]

DOI [BibTex]


Automatic LQR Tuning Based on Gaussian Process Optimization: Early Experimental Results
Automatic LQR Tuning Based on Gaussian Process Optimization: Early Experimental Results

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

Machine Learning in Planning and Control of Robot Motion Workshop at the IEEE/RSJ International Conference on Intelligent Robots and Systems (iROS), pages: , , Machine Learning in Planning and Control of Robot Motion Workshop, October 2015 (conference)

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. Preliminary results of a low-dimensional tuning problem highlight the method’s potential for automatic controller tuning on robotic platforms.

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PDF DOI Project Page [BibTex]

PDF DOI Project Page [BibTex]


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Stabilizing Novel Objects by Learning to Predict Tactile Slip

Veiga, F., van Hoof, H., Peters, J., Hermans, T.

In Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems, pages: 5065-5072, IROS, September 2015 (inproceedings)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Model-Free Probabilistic Movement Primitives for Physical Interaction

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

In Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems, pages: 2860-2866, IROS, September 2015 (inproceedings)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Combined Pose-Wrench and State Machine Representation for Modeling Robotic Assembly Skills

Wahrburg, A., Zeiss, S., Matthias, B., Peters, J., Ding, H.

In Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems, pages: 852-857, IROS, September 2015 (inproceedings)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Probabilistic Progress Prediction and Sequencing of Concurrent Movement Primitives

Manschitz, S., Kober, J., Gienger, M., Peters, J.

In Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems, pages: 449-455, IROS, September 2015 (inproceedings)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Reinforcement Learning vs Human Programming in Tetherball Robot Games

Parisi, S., Abdulsamad, H., Paraschos, A., Daniel, C., Peters, J.

In Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems, pages: 6428-6434, IROS, September 2015 (inproceedings)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Learning Motor Skills from Partially Observed Movements Executed at Different Speeds

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

In Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems, pages: 456-463, IROS, September 2015 (inproceedings)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


3D-printed Soft Microrobot for Swimming in Biological Fluids
3D-printed Soft Microrobot for Swimming in Biological Fluids

Qiu, T., Palagi, S., Fischer, P.

In Conf. Proc. IEEE Eng. Med. Biol. Soc., pages: 4922-4925, August 2015 (inproceedings)

Abstract
Microscopic artificial swimmers hold the potential to enable novel non-invasive medical procedures. In order to ease their translation towards real biomedical applications, simpler designs as well as cheaper yet more reliable materials and fabrication processes should be adopted, provided that the functionality of the microrobots can be kept. A simple single-hinge design could already enable microswimming in non-Newtonian fluids, which most bodily fluids are. Here, we address the fabrication of such single-hinge microrobots with a 3D-printed soft material. Firstly, a finite element model is developed to investigate the deformability of the 3D-printed microstructure under typical values of the actuating magnetic fields. Then the microstructures are fabricated by direct 3D-printing of a soft material and their swimming performances are evaluated. The speeds achieved with the 3D-printed microrobots are comparable to those obtained in previous work with complex fabrication procedures, thus showing great promise for 3D-printed microrobots to be operated in biological fluids.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Assessing human-human therapy kinematics for retargeting to human-robot therapy

Johnson, M. J., Christopher, S. M., Mohan, M., Mendonca, R.

In Proceedings of the IEEE International Conference on Rehabilitation Robotics (ICORR), Singapore, August 2015 (inproceedings)

Abstract
In this paper, we present experiments examining the accuracy of data collected from a Kinect sensor for capturing close interactive actions of a therapist with a patient during stroke rehabilitation. Our long-term goal is to map human-human interactions such as these patient-therapist ones onto human-robot interactions. In many robot interaction scenarios, the robot does not mimic interaction between two or more humans, which is a major part of stroke therapy. The Kinect works for functional tasks such as a reaching task where the interaction to be retargeted by the robot is minimal to none; though this data is not good for a functional task involving touching another person. We demonstrate that the noisy data from Kinect does not produce a system robust enough to be for remapping to a humanoid robot a therapit's movements when in contact with a person.

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DOI [BibTex]

DOI [BibTex]


Direct Loss Minimization Inverse Optimal Control
Direct Loss Minimization Inverse Optimal Control

Doerr, A., Ratliff, N., Bohg, J., Toussaint, M., Schaal, S.

In Proceedings of Robotics: Science and Systems, Rome, Italy, Robotics: Science and Systems XI, July 2015 (inproceedings)

Abstract
Inverse Optimal Control (IOC) has strongly impacted the systems engineering process, enabling automated planner tuning through straightforward and intuitive demonstration. The most successful and established applications, though, have been in lower dimensional problems such as navigation planning where exact optimal planning or control is feasible. In higher dimensional systems, such as humanoid robots, research has made substantial progress toward generalizing the ideas to model free or locally optimal settings, but these systems are complicated to the point where demonstration itself can be difficult. Typically, real-world applications are restricted to at best noisy or even partial or incomplete demonstrations that prove cumbersome in existing frameworks. This work derives a very flexible method of IOC based on a form of Structured Prediction known as Direct Loss Minimization. The resulting algorithm is essentially Policy Search on a reward function that rewards similarity to demonstrated behavior (using Covariance Matrix Adaptation (CMA) in our experiments). Our framework blurs the distinction between IOC, other forms of Imitation Learning, and Reinforcement Learning, enabling us to derive simple, versatile, and practical algorithms that blend imitation and reinforcement signals into a unified framework. Our experiments analyze various aspects of its performance and demonstrate its efficacy on conveying preferences for motion shaping and combined reach and grasp quality optimization.

am ics

PDF Video Project Page [BibTex]

PDF Video Project Page [BibTex]


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LMI-Based Synthesis for Distributed Event-Based State Estimation

Muehlebach, M., Trimpe, S.

In Proceedings of the American Control Conference, July 2015 (inproceedings)

Abstract
This paper presents an LMI-based synthesis procedure for distributed event-based state estimation. Multiple agents observe and control a dynamic process by sporadically exchanging data over a broadcast network according to an event-based protocol. In previous work [1], the synthesis of event-based state estimators is based on a centralized design. In that case three different types of communication are required: event-based communication of measurements, periodic reset of all estimates to their joint average, and communication of inputs. The proposed synthesis problem eliminates the communication of inputs as well as the periodic resets (under favorable circumstances) by accounting explicitly for the distributed structure of the control system.

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PDF DOI Project Page [BibTex]

PDF DOI Project Page [BibTex]


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Guaranteed H2 Performance in Distributed Event-Based State Estimation

Muehlebach, M., Trimpe, S.

In Proceeding of the First International Conference on Event-based Control, Communication, and Signal Processing, June 2015 (inproceedings)

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PDF DOI Project Page [BibTex]

PDF DOI Project Page [BibTex]


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On the Choice of the Event Trigger in Event-based Estimation

Trimpe, S., Campi, M.

In Proceeding of the First International Conference on Event-based Control, Communication, and Signal Processing, June 2015 (inproceedings)

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PDF DOI Project Page [BibTex]

PDF DOI Project Page [BibTex]


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Toward a large-scale visuo-haptic dataset for robotic learning

Burka, A., Hu, S., Krishnan, S., Kuchenbecker, K. J., Hendricks, L. A., Gao, Y., Darrell, T.

In Proc. CVPR Workshop on the Future of Datasets in Vision, 2015 (inproceedings)

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Project Page [BibTex]

Project Page [BibTex]


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Detecting Lumps in Simulated Tissue via Palpation with a BioTac

Hui, J., Block, A., Kuchenbecker, K. J.

In Proc. IEEE World Haptics Conference, 2015, Work-in-progress paper. Poster presentation given by Hui (inproceedings)

hi

[BibTex]

[BibTex]


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Analysis of the Instrument Vibrations and Contact Forces Caused by an Expert Robotic Surgeon Doing FRS Tasks

Brown, J. D., O’Brien, C., Miyasaka, K., Dumon, K. R., Kuchenbecker, K. J.

In Proc. Hamlyn Symposium on Medical Robotics, pages: 75-76, London, England, June 2015, Poster presentation given by Brown (inproceedings)

hi

[BibTex]

[BibTex]


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Should Haptic Texture Vibrations Respond to User Force and Speed?

Culbertson, H., Kuchenbecker, K. J.

In IEEE World Haptics Conference, pages: 106 - 112, Evanston, Illinois, USA, June 2015, Oral presentation given by Culbertson (inproceedings)

hi

[BibTex]

[BibTex]


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Enabling the Baxter Robot to Play Hand-Clapping Games

Fitter, N. T., Neuburger, M., Kuchenbecker, K. J.

In Proc. IEEE World Haptics Conference, June 2015, Work-in-progress paper. Poster presentation given by Fitter (inproceedings)

hi

[BibTex]

[BibTex]


Leveraging Big Data for Grasp Planning
Leveraging Big Data for Grasp Planning

Kappler, D., Bohg, B., Schaal, S.

In Proceedings of the IEEE International Conference on Robotics and Automation, May 2015 (inproceedings)

Abstract
We propose a new large-scale database containing grasps that are applied to a large set of objects from numerous categories. These grasps are generated in simulation and are annotated with different grasp stability metrics. We use a descriptive and efficient representation of the local object shape at which each grasp is applied. Given this data, we present a two-fold analysis: (i) We use crowdsourcing to analyze the correlation of the metrics with grasp success as predicted by humans. The results show that the metric based on physics simulation is a more consistent predictor for grasp success than the standard ε-metric. The results also support the hypothesis that human labels are not required for good ground truth grasp data. Instead the physics-metric can be used to generate datasets in simulation that may then be used to bootstrap learning in the real world. (ii) We apply a deep learning method and show that it can better leverage the large-scale database for prediction of grasp success compared to logistic regression. Furthermore, the results suggest that labels based on the physics-metric are less noisy than those from the ε-metric and therefore lead to a better classification performance.

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PDF data DOI Project Page [BibTex]

PDF data DOI Project Page [BibTex]


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Event-based Estimation and Control for Remote Robot Operation with Reduced Communication

Trimpe, S., Buchli, J.

In Proceedings of the IEEE International Conference on Robotics and Automation, May 2015 (inproceedings)

Abstract
An event-based communication framework for remote operation of a robot via a bandwidth-limited network is proposed. The robot sends state and environment estimation data to the operator, and the operator transmits updated control commands or policies to the robot. Event-based communication protocols are designed to ensure that data is transmitted only when required: the robot sends new estimation data only if this yields a significant information gain at the operator, and the operator transmits an updated control policy only if this comes with a significant improvement in control performance. The developed framework is modular and can be used with any standard estimation and control algorithms. Simulation results of a robotic arm highlight its potential for an efficient use of limited communication resources, for example, in disaster response scenarios such as the DARPA Robotics Challenge.

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PDF DOI Project Page [BibTex]

PDF DOI Project Page [BibTex]


The Coordinate Particle Filter - A novel Particle Filter for High Dimensional Systems
The Coordinate Particle Filter - A novel Particle Filter for High Dimensional Systems

Wüthrich, M., Bohg, J., Kappler, D., Pfreundt, C., Schaal, S.

In Proceedings of the IEEE International Conference on Robotics and Automation, May 2015 (inproceedings)

Abstract
Parametric filters, such as the Extended Kalman Filter and the Unscented Kalman Filter, typically scale well with the dimensionality of the problem, but they are known to fail if the posterior state distribution cannot be closely approximated by a density of the assumed parametric form. For nonparametric filters, such as the Particle Filter, the converse holds. Such methods are able to approximate any posterior, but the computational requirements scale exponentially with the number of dimensions of the state space. In this paper, we present the Coordinate Particle Filter which alleviates this problem. We propose to compute the particle weights recursively, dimension by dimension. This allows us to explore one dimension at a time, and resample after each dimension if necessary. Experimental results on simulated as well as real data con- firm that the proposed method has a substantial performance advantage over the Particle Filter in high-dimensional systems where not all dimensions are highly correlated. We demonstrate the benefits of the proposed method for the problem of multi-object and robotic manipulator tracking.

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arXiv Video Bayesian Filtering Framework Bayesian Object Tracking DOI Project Page [BibTex]


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Using IMU Data to Teach a Robot Hand-Clapping Games

Fitter, N. T., Kuchenbecker, K. J.

In Proc. IEEE Haptics Symposium, pages: 353-355, April 2015, Work-in-progress paper. Poster presentation given by Fitter (inproceedings)

hi

[BibTex]

[BibTex]


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Haptic Feedback in Transoral Robotic Surgery: A Feasibility Study

Bur, A. M., Gomez, E. D., Rassekh, C. H., Newman, J. G., Weinstein, G. S., Kuchenbecker, K. J.

In Proc. Annual Meeting of the Triological Society at COSM, April 2015, Poster presentation given by Bur (inproceedings)

hi

[BibTex]

[BibTex]


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Understanding the Geometry of Workspace Obstacles in Motion Optimization

Ratliff, N., Toussaint, M., Schaal, S.

In Proceedings of the IEEE International Conference on Robotics and Automation, March 2015 (inproceedings)

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PDF Video Project Page [BibTex]

PDF Video Project Page [BibTex]


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Human Machine Interface for Dexto Eka: - The humanoid robot

Kumra, S., Mohan, M., Gupta, S., Vaswani, H.

In Proceedings of the IEEE International Conference on Robotics, Automation, Control and Embedded Systems (RACE), Chennai, India, Febuary 2015 (inproceedings)

Abstract
This paper illustrates hybrid control system of the humanoid robot, Dexto:Eka: focusing on the dependent or slave mode. Efficiency of any system depends on the fluid operation of its control system. Here, we elucidate the control of 12 DoF robotic arms and an omnidirectional mecanum wheel drive using an exo-frame, and a Graphical User Interface (GUI) and a control column. This paper comprises of algorithms, control mechanisms and overall flow of execution for the regulation of robotic arms, graphical user interface and locomotion.

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DOI [BibTex]

DOI [BibTex]


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Conception and development of Dexto:Eka: The Humanoid Robot - Part IV

Kumra, S., Mohan, M., Vaswani, H., Gupta, S.

In Proceedings of the IEEE International Conference on Robotics, Automation, Control and Embedded Systems (RACE), Febuary 2015 (inproceedings)

Abstract
This paper elucidates the fourth phase of the development of `Dexto:Eka: - The Humanoid Robot'. It lays special emphasis on the conception of the locomotion drive and the development of vision based system that aids navigation and tele-operation. The first three phases terminated with the completion of two robotic arms with six degrees of freedom each, structural development and the creation of a human machine interface that included an exo-frame, a control column and a graphical user interface. This phase also involved the enhancement of the exo-frame to a vision based system using a Kinect camera. The paper also focuses on the reasons behind choosing the locomotion drive and the benefits it has.

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DOI [BibTex]

DOI [BibTex]


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Design and Validation of a Practical Simulator for Transoral Robotic Surgery

Bur, A. M., Gomez, E. D., Chalian, A. A., Newman, J. G., Weinstein, G. S., Kuchenbecker, K. J.

In Proc. Society for Robotic Surgery Annual Meeting: Transoral Program, (T8), February 2015, Oral presentation given by Bur (inproceedings)

hi

[BibTex]

[BibTex]


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Learning of Non-Parametric Control Policies with High-Dimensional State Features

van Hoof, H., Peters, J., Neumann, G.

In Proceedings of the 18th International Conference on Artificial Intelligence and Statistics, 38, pages: 995–1003, (Editors: Lebanon, G. and Vishwanathan, S.V.N. ), JMLR, AISTATS, 2015 (inproceedings)

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link (url) [BibTex]

link (url) [BibTex]


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Data-Driven Online Decision Making for Autonomous Manipulation

Kappler, D., Pastor, P., Kalakrishnan, M., Wuthrich, M., Schaal, S.

In Proceedings of Robotics: Science and Systems, Rome, Italy, 2015 (inproceedings)

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Project Page [BibTex]

Project Page [BibTex]


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

Mainprice, J., Hayne, R., Berenson, D.

In Proceedings of the IEEE International Conference on Robotics and Automation, 2015 (inproceedings)

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Project Page [BibTex]

Project Page [BibTex]


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Semi-Autonomous 3rd-Hand Robot

Lopes, M., Peters, J., Piater, J., Toussaint, M., Baisero, A., Busch, B., Erkent, O., Kroemer, O., Lioutikov, R., Maeda, G., Mollard, Y., Munzer, T., Shukla, D.

In Workshop on Cognitive Robotics in Future Manufacturing Scenarios, European Robotics Forum, 2015 (inproceedings)

am ei

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)

ev

[BibTex]

[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)

am ei

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)

am ei

link (url) [BibTex]

link (url) [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)

ev

[BibTex]

[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)

am ei

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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


Policy Learning with Hypothesis Based Local Action Selection
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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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)

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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)

am ei

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]