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2. AutoMate: Specialist and Generalist Assembly Policies over Diverse Geometries
 
 # AutoMate: Specialist and Generalist Assembly Policies over Diverse Geometries

  ![](/sites/default/files/styles/wide/public/publications/automate_pic.png?itok=DJC3x-yz)

 Robotic assembly for high-mixture settings requires adaptivity to diverse parts and poses, which is an open challenge. Meanwhile, in other areas of robotics, large models and sim-to-real have led to tremendous progress.

Inspired by such work, we present **AutoMate**, a learning framework and system that consists of 4 parts: 1) a dataset of 100 assemblies compatible with simulation and the real world, along with parallelized simulation environments for policy learning, 2) a novel simulation-based approach for learning specialist (i.e., part-specific) policies and generalist (i.e., unified) assembly policies, 3) demonstrations of specialist policies that individually solve 80 assemblies with ≈80%+ success rates in simulation, as well as a generalist policy that jointly solves 20 assemblies with an 80%+ success rate, and 4) zero-shot sim-to-real transfer that achieves similar (or better) performance than simulation, including on perception-initialized assembly.

To our knowledge, **AutoMate** provides the first simulation-based framework for learning specialist and generalist policies over a wide range of assemblies, as well as the first system demonstrating zero-shot sim-to-real transfer over such a range.



 ## Authors



Bingjie Tang (University of Southern California)

[Iretiayo Akinola](/person/iretiayo-akinola)

[Jie Xu](/person/jie-xu)

[Bowen Wen](/person/bowen-wen)

Ankur Handa (NVIDIA)

Karl Van Wyk (NVIDIA)

Dieter Fox (NVIDIA)

Gaurav S. Sukhatme (University of Southern California)

[Fabio Ramos](/person/fabio-ramos)

[Yashraj Narang](/person/yashraj-narang)

 

 

 ## Publication Date



Monday, July 15, 2024

 

 ## Published in



[Robotics: Science and Systems (RSS) 2024](https://roboticsconference.org/2024/)

 

 ## Research Area



[Artificial Intelligence and Machine Learning ](/research-area/machine-learning-artificial-intelligence)

[Robotics](/research-area/robotics)

 

 

 ## External Links



[Project Website](https://bingjietang718.github.io/automate/)