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Learn how we have evolved Aloha to deliver more performance and more value than ever.

At Trossen Robotics , we have been at the forefront of developing affordable, high-performance robotic platforms  for researchers,...

The ALOHA 2.0 package brings a transformative update to the world of robotics, introducing modular configurations and enhanced flexibility.

Fireside chat with Remi Cadene, from Hugging Face, and Shantanu Parab, from Trossen Robotics.

As machine learning continues to expand into robotics, the need for efficient and accessible tools has never been greater. In our latest...

We are thrilled to announce the launch of the Trossen Robotics Machine Learning Community—a one-stop destination for all things related to r

Discover how bimanual robots use the ACT model for precision peg-insertion. 80% success rate! Access datasets & models on Hugging Face.

We are thrilled to announce full support for LeRobot with our Aloha Robotic Machine Learning Kits, now available on Hugging Face!

Discover how diffusion models in imitation learning help robots mimic human actions, handle noise, and perform complex tasks efficiently.

CrossFormers introduce a transformer-based policy that can control a wide variety of robots across different tasks, including manipulation,

Discover how variations in data collection impact imitation learning with the Aloha Kit. Explore experiments and access datasets on Hugging

Bi-ACT builds upon ACT with an approach that incorporates both position and force information.

Imitation learning is essential in robotics for its ability to quickly and safely teach robots complex tasks.

Auto Encoders, VAEs, and CVAEs in robotic machine learning help reduce data complexity, generate new data, and improve precision.

Imitation learning (IL) enables robots to mimic human actions, evolving from basic Behavior Cloning to advanced methods like Deep Imitation.