Columbia University & DeepMind Enhance General Part Assembly Planning Using a Transformer-based Model

In a new paper General Part Assembly Planning, a research team from Columbia University and Google DeepMind introduces General Part Assembly Transformer (GPAT), a transformer-based model for assembly planning that has strong generalization capability to automatically estimate novel and diverse target and part shapes.

ai artificial intelligence assembly assembly planning columbia university deepmind deep-neural-networks diverse general google google deepmind machine learning machine learning & data science ml novel paper part planning research research team robotics team technology transformer transformers university