4 papers · 1 filter
Imitation from Heterogeneous Demonstrations using Grounded Latent-Action World Models
Tianyou Wang, Anson Lei, Joe Watson +1
Imitation learning has emerged as a powerful paradigm for learning visuomotor policies, but its generalisation and stability are limited by the scale and quality of demonstration d…
Global Tensor Motion Planning
An T. Le, Kay Hansel, João Carvalho +5
Batch planning is increasingly necessary to quickly produce diverse and quality motion plans for downstream learning applications, such as distillation and imitation learning. This…
Towards Safe Robot Foundation Models Using Inductive Biases
Maximilian Tölle, Theo Gruner, Daniel Palenicek +6
Safety is a critical requirement for the real-world deployment of robotic systems. Unfortunately, while current robot foundation models show promising generalization capabilities a…
Towards Safe Robot Foundation Models
Maximilian Tölle, Theo Gruner, Daniel Palenicek +5
Robot foundation models hold the potential for deployment across diverse environments, from industrial applications to household tasks. While current research focuses primarily on…