Latent Plans for Task-Agnostic Offline Reinforcement Learning

1 code implementation • 19 Sep 2022 • Erick Rosete-Beas, Oier Mees, Gabriel Kalweit, Joschka Boedecker, Wolfram Burgard

Concretely, we combine a low-level policy that learns latent skills via imitation learning and a high-level policy learned from offline reinforcement learning for skill-chaining the latent behavior priors.

Imitation Learning reinforcement-learning +1

T3VIP: Transformation-based 3D Video Prediction

1 code implementation • 19 Sep 2022 • Iman Nematollahi, Erick Rosete-Beas, Seyed Mahdi B. Azad, Raghu Rajan, Frank Hutter, Wolfram Burgard

To the best of our knowledge, our model is the first generative model that provides an RGB-D video prediction of the future for a static camera.

Hyperparameter Optimization Video Prediction

CALVIN: A Benchmark for Language-Conditioned Policy Learning for Long-Horizon Robot Manipulation Tasks

1 code implementation • 6 Dec 2021 • Oier Mees, Lukas Hermann, Erick Rosete-Beas, Wolfram Burgard

We show that a baseline model based on multi-context imitation learning performs poorly on CALVIN, suggesting that there is significant room for developing innovative agents that learn to relate human language to their world models with this benchmark.

Continuous Control Imitation Learning +3

Robot Skill Adaptation via Soft Actor-Critic Gaussian Mixture Models

no code implementations • 25 Nov 2021 • Iman Nematollahi, Erick Rosete-Beas, Adrian Röfer, Tim Welschehold, Abhinav Valada, Wolfram Burgard

A core challenge for an autonomous agent acting in the real world is to adapt its repertoire of skills to cope with its noisy perception and dynamics.