Python code for Physical Human-Robot Collaboration (DMPs): https://gitlab.com/lukapeternel/PHRC

This repository includes code for the Physical Human-Robot Collaboration system that inlcudes human electromyography (EMG) and a hybrid force/impedance controller based on the work in Peternel, L., Tsagarakis, N., & Ajoudani, A. (2017). A human–robot co-manipulation approach based on human sensorimotor information. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 25(7), 811-822, as well as code for the muscle fatigue model based on the work in Peternel, L., Tsagarakis, N., Caldwell, D., & Ajoudani, A. (2018). Robot adaptation to human physical fatigue in human–robot co-manipulation. Autonomous Robots, 42(5), 1011-1021.

A comprehensive collection of codes for Dynamic Movement Primitives (DMPs): https://gitlab.com/dmp-codes-collection

This repository is a result of a paper published in Saveriano, M., Abu-Dakka, F. J., Kramberger, A., & Peternel, L. (2021). Dynamic movement primitives in robotics: A tutorial survey. arXiv preprint arXiv:2102.03861.

Python code for Interactive Learning of Stiffness and Attractors (ILoSA): https://github.com/franzesegiovanni/ILoSA

This repository (by Giovanni Franzese and Anna Mészáros) is a result of research that was published in Franzese, G., Mészáros, A., Peternel, L., & Kober, J. (2021, January). ILoSA: Interactive learning of stiffness and attractors. In 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 7778-7785).