The Rise of Diffusion Models in Imitation Learning
Discover how diffusion models in imitation learning help robots mimic human actions, handle noise, and perform complex tasks efficiently.
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Latest News
- 5 days ago
Machine Learning Series - Crossformers Whitepaper Review
CrossFormers introduce a transformer-based policy that can control a wide variety of robots across different tasks, including manipulation,
- Sep 3
The Impact of Data Quality on Training Imitation Learning Models: Experiments with the Aloha Kit
Discover how variations in data collection impact imitation learning with the Aloha Kit. Explore experiments and access datasets on Hugging
- Aug 27
Machine Learning Series - BiACT Whitepaper Review
Bi-ACT builds upon ACT with an approach that incorporates both position and force information.
- Aug 27
Machine Learning Series - ACT Action Chunking Transformers
Imitation learning is essential in robotics for its ability to quickly and safely teach robots complex tasks.
- Aug 27
Machine Learning Series - Encoders | Auto, Variational and Conditional
Auto Encoders, VAEs, and CVAEs in robotic machine learning help reduce data complexity, generate new data, and improve precision.
- Aug 22
Revolutionizing Robot Behavior: How Transformers Elevate Imitation Learning with Action Chunking
Imitation learning (IL) enables robots to mimic human actions, evolving from basic Behavior Cloning to advanced methods like Deep Imitation.
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