Memory Architecture and Robotic Learning

This chapter explores the necessity of a dedicated memory-based architecture for robotic learning, addressing challenges related to long context dependencies and compounding errors. It further discusses task design for evaluating robots' memory capabilities, the impact of trajectory modeling, and advanced training methodologies that enhance task execution efficiency.