Advancing Robotics with Vision Language Models

This chapter explores the application of large foundation models and vision language models to enhance robotics tasks through automated learning. It discusses how models can utilize progress estimation to filter data and improve task completion by analyzing video frames in a structured manner. The chapter also introduces the Value Order Correlation (VOC) metric for evaluating task progress while emphasizing the potential of self-supervised learning and multi-modal approaches in developing more effective robotics systems.