Project page for work on Learning Complex Sequential Tasks from Demonstrations
This project is maintained by epfl-lasa
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Following we list all of the code repositories made available for this project, including:
Code for Automatic Segmentation and Primitive Action Discovery in MATLAB
https://github.com/nbfigueroa/ICSC-HMM
Code for Learning Position+Orientation Coupled Dynamical System (CDS) in MATLAB
https://github.com/alpais/cds_model_learning_generic
Code for Execution of Position+Orientation Coupled Dynamical System (CDS) in C++
https://github.com/epfl-lasa/coupled-dynamical-systems
Code for Task Planning of Uni-Manual Pizza Dough Rolling for KUKA LWR 4+ in ROS
https://github.com/epfl-lasa/task-motion-planning-cds
Code for Task Planning of Bi-Manual Vegetable Peeling for 2 KUKA LWR 4+ in ROS
https://github.com/epfl-lasa/bimanual-task-motion-planning
[1] Figueroa, N. and Billard, A. (2018) Transform-Invariant Non-Parametric Clustering of Covariance Matrices and its Application to Unsupervised Joint Segmentation and Action Discovery. In submission. arXiv link
[2] Figueroa, N., Pais, A. L. and Billard, A. (2016) Learning Complex Sequential Tasks from Demonstration: A Pizza Dough Rolling Case Study. In Proceedings of the 2016 ACM/IEEE International Conference on Human-Robot Interaction. HRI Pioneers Workshop. link
[3] Beetz, M., Bessler, D., Winkler, J., Bartels, G., Billard, A., Figueroa, N., Pais, A. L. and et al. (2016) Open Robotics Research Using Web-based Knowledge Services. In Proceedings of the International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, 2016. link
[4] Figueroa, N. and Billard, A. (2017) Learning Complex Manipulation Tasks from Heterogeneous and Unstructured Demonstrations. In Proceedings of Workshop on Synergies between Learning and Interaction. IROS’2017 link
Nadia Figueroa (nadia.figueroafernandez AT epfl dot ch)
This work was supported by the EU project Robohow.