- Manschitz, S.; Gienger, M.; Kober, J.; Peters, J. (2018). Mixture of Attractors: A novel Movement Primitive Representation for Learning Motor Skills from Demonstrations, IEEE Robotics and Automation Letters (RA-L), 3, 2, pp.926-933.
- Manschitz, S. (2017). Learning Sequential Skills for Robot Manipulation Tasks, PhD Thesis.
- Manschitz, S.; Kober, J.; Gienger, M.; Peters, J. (2015). Learning Movement Primitive Attractor Goals and Sequential Skills from Kinesthetic Demonstrations, Robotics and Autonomous Systems, 74, pp.97-107.
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- Guler, B.; Pompetzki, K.; Manschitz, S.; Peters, J. (2025). Towards Assistive Teleoperation for Knot Untangling, German Robotics Conference (GRC).
- Manschitz, S.; Guler, B.; Ma, W.; Ruiken, D. (2025). Sampling-Based Grasp and Collision Prediction for Assisted Teleoperation, IEEE International Conference on Robotics and Automation (ICRA).
- Manschitz, S.; Gienger, M.; Kober, J.; Peters, J. (2016). Probabilistic Decomposition of Sequential Force Interaction Tasks into Movement Primitives, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
- Manschitz, S.; Kober, J.; Gienger, M.; Peters, J. (2015). Probabilistic Progress Prediction and Sequencing of Concurrent Movement Primitives, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
- Manschitz, S.; Kober, J.; Gienger, M.; Peters, J. (2014). Learning to Unscrew a Light Bulb from Demonstrations, Proceedings of ISR/ROBOTIK 2014.
- Manschitz, S.; Kober, J.; Gienger, M.; Peters, J. (2014). Learning to Sequence Movement Primitives from Demonstrations, Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS).
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