382 citations · 801 across the 48 of their papers we have counts for
5 papers · 1 filter
Action-Conditional Recurrent Kalman Networks For Forward and Inverse Dynamics Learning
Vaisakh Shaj, Philipp Becker, Dieter Buchler +5
Estimating accurate forward and inverse dynamics models is a crucial component of model-based control for sophisticated robots such as robots driven by hydraulics, artificial muscl…
Imitation Learning for Autonomous Trajectory Learning of Robot Arms in Space
RB Ashith Shyam, Zhou Hao, Umberto Montanaro +1
This work adds on to the on-going efforts to provide more autonomy to space robots. Here the concept of programming by demonstration or imitation learning is used for trajectory pl…
Non-Adversarial Imitation Learning and its Connections to Adversarial Methods
Oleg Arenz, Gerhard Neumann
Many modern methods for imitation learning and inverse reinforcement learning, such as GAIL or AIRL, are based on an adversarial formulation. These methods apply GANs to match the…
Probabilistic approach to physical object disentangling
Joni Pajarinen, Oleg Arenz, Jan Peters +1
Physically disentangling entangled objects from each other is a problem encountered in waste segregation or in any task that requires disassembly of structures. Often there are no…
Expected Information Maximization: Using the I-Projection for Mixture Density Estimation
Philipp Becker, Oleg Arenz, Gerhard Neumann
Modelling highly multi-modal data is a challenging problem in machine learning. Most algorithms are based on maximizing the likelihood, which corresponds to the M(oment)-projection…