Perception

Convolutional Neural Network (CNN)

A convolutional neural network is a neural architecture that applies learned convolutional filters with shared weights across spatial positions, building translation-equivariant hierarchies of visual features. From LeNet through AlexNet (2012) and ResNet (2015), CNNs drove the deep learning revolution in computer vision and remain standard visual encoders in robot policies, including the ResNet backbones of many behavior cloning and diffusion policy implementations, though vision transformers now rival them.

Why it matters for physical AI

CNN encoders remain a compute-efficient choice for real-time visuomotor policies on embedded hardware, and their inductive biases help when robot datasets are too small to train transformers from scratch.