Information maximizing curriculum: A curriculum-based approach for learning versatile skills

D Blessing, O Celik, X Jia, M Reuss… - Advances in …, 2024 - proceedings.neurips.cc
Imitation learning uses data for training policies to solve complex tasks. However, when the
training data is collected from human demonstrators, it often leadsto multimodal distributions …

ARCADE: Scalable Demonstration Collection and Generation via Augmented Reality for Imitation Learning

Y Yang, B Ikeda, G Bertasius, D Szafir - arXiv preprint arXiv:2410.15994, 2024 - arxiv.org
Robot Imitation Learning (IL) is a crucial technique in robot learning, where agents learn by
mimicking human demonstrations. However, IL encounters scalability challenges stemming …

Augmented Reality Demonstrations for Scalable Robot Imitation Learning

Y Yang, B Ikeda, G Bertasius, D Szafir - arXiv preprint arXiv:2403.13910, 2024 - arxiv.org
Robot Imitation Learning (IL) is a widely used method for training robots to perform
manipulation tasks that involve mimicking human demonstrations to acquire skills. However …

Variational Distillation of Diffusion Policies into Mixture of Experts

H Zhou, D Blessing, G Li, O Celik, X Jia… - arXiv preprint arXiv …, 2024 - arxiv.org
This work introduces Variational Diffusion Distillation (VDD), a novel method that distills
denoising diffusion policies into Mixtures of Experts (MoE) through variational inference …

Self-learning and autonomously adapting manufacturing equipment for the circular factory

J Fleischer, F Zanger, V Schulze… - at …, 2024 - degruyter.com
The integration of both linear and circular processes in one production system poses
significant challenges. In particular, the reprocessing of end-of-life products is associated …