Robotic Ultra-Long-Horizon Manipulation Skills via Human-guided Lifelong Code Generation
The framework addresses limitations in AI code generation for long robotic tasks by using a human-in-the-loop approach. It learns skills through interactive feedback, extends these skills over time to handle new variations, and uses retrieval augmented generation to plan complex, multi-step maneuvers. This results in high success rates and significant efficiency gains for extremely long manipulation challenges.