Moravec's Paradox and the Robot Olympics

This post details the fine-tuning of the π0.6 robotic foundation model to address a set of 'Robot Olympics' manipulation tasks. It demonstrates initial solutions for 3 out of 5 proposed categories, achieving 'gold medal' status in tasks like opening a self-closing door, using a key, and cleaning a greasy pan. The contribution lies in showcasing the model's ability to generalize to novel, everyday physical tasks with under 9 hours of data collection per task, significantly outperforming a baseline VLM. The post also discusses the challenges of physical intelligence and the importance of large-scale robotic pre-training for achieving such capabilities.