Meeting Details
Date : 1st September 2022
Time : 11:00 – 12:00
Location : Chair of CPS, Montanuniverität Leoben
Participants: Univ.-Prof. Dr. Elmar Rueckert, Vedant Dave
Agenda
- Learning Consistent Forward and Inverse Dynamics.
Topic 1: Learning Forward and Inverse Dynamics with Cycle Consistency
- Develop a framework to learn forward and inverse model of the system simultaneously.
- Search tasks where both models are required.
- Test on the datatset from [1].
Topic 2: Binding Simulation and Reality Gap
- Working with forward model in the simulation and correcting it with inverse model from real system.
- Develop tasks for contact
Literature
Inverse Dynamic Predictions
- Elmar Rueckert et al. “Learning inverse dynamics models in O(n) time with LSTM networks”. In: 2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids). 2017, pp. 811–816.
- Vaisakh Shaj et al. “Action-Conditional Recurrent Kalman Networks For Forward and Inverse Dynamics Learning”. In: Proceedings of the 2020 Conference on Robot Learning. Ed. by Jens Kober, Fabio Ramos, and Claire Tomlin. Vol. 155. Proceedings of Machine Learning Research. PMLR, Nov. 2021, pp. 765–781.
- Moritz Reuss et al. “End to-End Learning of Hybrid Inverse Dynamics Models for Precise and Compliant Impedance Control”. In: Proceedings of Robotics: Science and Systems. New York City, NY, USA, June 2022.
Next Meeting
TBD