Offline Hierarchical Reinforcement Learning for Long-Horizon Trajectory Planning with Diffusion-Based Options Under LTL Constraints

DOPPLER, a novel hierarchical reinforcement learning framework, leverages diffusion models to generate options for complex, long-horizon robot trajectory planning under Linear Temporal Logic (LTL) constraints in an offline setting.