Daniel Kappler studied Computer-Science at the Karlsruhe Institute of Technology (KIT), in Germany, focusing on machine learning and robotics. He was a visiting researcher at the Robotics Institute at Carnegie Mellon University (CMU) in 2010, where he worked on object manipulation prior to grasping. In 2012 he received his Diploma, conducted as a visiting researcher at the Istituto Italiano di Tecnologia (IIT), for his work on transfer learning. Daniel joined the Autonomous Motion Department at the Max-Planck Institute for Intelligent Systems in November 2012, where he is currently pursuing a PhD. His main research interests are in data-driven learning techniques for dexterous robot manipulation, including perception of objects at speed, grasp planning for unknown objects, and online sensor prediction for real-time decision making.
Humanoid Robotics Grasping and Manipulation Sensor Prediction Representation Learning Machine Learning
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Merzic, H., Bogdanovic, M., Kappler, D., Righetti, L., Bohg, J.
Leveraging Contact Forces for Learning to Grasp
arXiv, September 2018, Submitted to ICRA'19 (article) Submitted
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Kappler, D., Meier, F., Issac, J., Mainprice, J., Garcia Cifuentes, C., Wüthrich, M., Berenz, V., Schaal, S., Ratliff, N., Bohg, J.
Real-time Perception meets Reactive Motion Generation
IEEE Robotics and Automation Letters, 3(3):1864-1871, July 2018 (article)
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Meier, F., Kappler, D., Schaal, S.
Online Learning of a Memory for Learning Rates
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2018, IEEE, International Conference on Robotics and Automation, May 2018, accepted (inproceedings)
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Kappler, D., Meier, F., Ratliff, N., Schaal, S.
A New Data Source for Inverse Dynamics Learning
In Proceedings IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, Piscataway, NJ, USA, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), September 2017 (inproceedings)
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Rubert, C., Kappler, D., Morales, A., Schaal, S., Bohg, J.
On the relevance of grasp metrics for predicting grasp success
In Proceedings of the IEEE/RSJ International Conference of Intelligent Robots and Systems, September 2017 (inproceedings) Accepted
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Prokudin, S., Kappler, D., Nowozin, S., Gehler, P.
Learning to Filter Object Detections
In Pattern Recognition: 39th German Conference, GCPR 2017, Basel, Switzerland, September 12–15, 2017, Proceedings, pages: 52-62, Springer International Publishing, Cham, 2017 (inbook)
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Wüthrich, M., Trimpe, S., Garcia Cifuentes, C., Kappler, D., Schaal, S.
A New Perspective and Extension of the Gaussian Filter
The International Journal of Robotics Research, 35(14):1731-1749, December 2016 (article)
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Kloss, A., Kappler, D., Lensch, H. P. A., Butz, M. V., Schaal, S., Bohg, J.
Learning Where to Search Using Visual Attention
Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems, IEEE, IROS, October 2016 (conference)
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Gadde, R., Jampani, V., Kiefel, M., Kappler, D., Gehler, P.
Superpixel Convolutional Networks using Bilateral Inceptions
In European Conference on Computer Vision (ECCV), Lecture Notes in Computer Science, Springer, 14th European Conference on Computer Vision, October 2016 (inproceedings)
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Lassner, C., Kappler, D., Kiefel, M., Gehler, P.
Barrista - Caffe Well-Served
In ACM Multimedia Open Source Software Competition, ACM OSSC16, October 2016 (inproceedings)
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Bohg, J., Kappler, D., Meier, F., Ratliff, N., Mainprice, J., Issac, J., Wüthrich, M., Garcia Cifuentes, C., Berenz, V., Schaal, S.
Interlocking Perception-Action Loops at Multiple Time Scales - A System Proposal for Manipulation in Uncertain and Dynamic Environments
In International Workshop on Robotics in the 21st century: Challenges and Promises, September 2016 (inproceedings)
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Ratliff, N., Meier, F., Kappler, D., Schaal, S.
DOOMED: Direct Online Optimization of Modeling Errors in Dynamics
arXiv preprint arXiv:1608.00309, August 2016 (article)
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Widmaier, F., Kappler, D., Schaal, S., Bohg, J.
Robot Arm Pose Estimation by Pixel-wise Regression of Joint Angles
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2016, IEEE, IEEE International Conference on Robotics and Automation, May 2016 (inproceedings)
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Kappler, D., Schaal, S., Bohg, J.
Optimizing for what matters: the Top Grasp Hypothesis
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2016, IEEE, IEEE International Conference on Robotics and Automation, May 2016 (inproceedings)
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Bohg, J., Kappler, D., Schaal, S.
Exemplar-based Prediction of Object Properties from Local Shape Similarity
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2016, IEEE, IEEE International Conference on Robotics and Automation, May 2016 (inproceedings)
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Meier, F., Kappler, D., Ratliff, N., Schaal, S.
Towards Robust Online Inverse Dynamics Learning
Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems, IEEE, IROS, 2016 (conference) Accepted
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Kappler, D., Bohg, B., Schaal, S.
Leveraging Big Data for Grasp Planning
In Proceedings of the IEEE International Conference on Robotics and Automation, May 2015 (inproceedings)
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Wüthrich, M., Bohg, J., Kappler, D., Pfreundt, C., Schaal, S.
The Coordinate Particle Filter - A novel Particle Filter for High Dimensional Systems
In Proceedings of the IEEE International Conference on Robotics and Automation, May 2015 (inproceedings)
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Kappler, D., Pastor, P., Kalakrishnan, M., Wuthrich, M., Schaal, S.
Data-Driven Online Decision Making for Autonomous Manipulation
In Proceedings of Robotics: Science and Systems, Rome, Italy, 2015 (inproceedings)
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Wüthrich, M., Trimpe, S., Kappler, D., Schaal, S.
A New Perspective and Extension of the Gaussian Filter
In Robotics: Science and Systems, 2015 (inproceedings)