Goal-Conditioned Variational Autoencoder Trajectory Primitives with Continuous and Discrete Latent Codes

no code implementations • 9 Dec 2019 • Takayuki Osa, Shuhei Ikemoto

The learned decoder can be used as a motion planner in which the user can specify the goal position and the trajectory types by setting the latent variables.

Data Augmentation Imitation Learning +1

Learning Interactive Behaviors for Musculoskeletal Robots Using Bayesian Interaction Primitives

no code implementations • 15 Aug 2019 • Joseph Campbell, Arne Hitzmann, Simon Stepputtis, Shuhei Ikemoto, Koh Hosoda, Heni Ben Amor

Musculoskeletal robots that are based on pneumatic actuation have a variety of properties, such as compliance and back-drivability, that render them particularly appealing for human-robot collaboration.

Response Generation