End-to-End Learning

Training a single neural network to map directly from raw sensor inputs (images, proprioception) to robot actions, without hand-designed intermediate representations or modular pipelines. End-to-end learning avoids the information bottleneck of modular systems but requires more training data and is harder to interpret. VLA models represent the frontier of end-to-end robot learning.