hierarchical robot planning

In this paper, we use deep learning to identify critical regions and automatically construct hierarchical state and action abstractions. We use these hierarchical abstractions with a multi-source mutli-directional hierarchical planner to compute solutions for robot planning problem.

In this paper, we propose unified framework based on deep learning that learns sound abstractiosn for complex robot planning problems and uses it to efficiently perform hierarchical planning.