Robotic Long-Horizon Manipulation with Bayesian Non-parametric Skill Priors
HELIOS is a framework for long-horizon manipulation that uses Bayesian non-parametric skill priors to guide reinforcement learning. It pretrains a flexible skill representation model and then integrates it into a hierarchical RL system. This approach significantly improves performance and generalization on complex, extended tasks by dynamically capturing the necessary skills.