Hierarchies of Planning and Reinforcement Learning for Robot Navigation
Jan Wöhlke,Felix Schmitt,Herke van Hoof,Jan Wöhlke,Felix Schmitt,Herke van Hoof
Solving robotic navigation tasks via reinforcement learning (RL) is challenging due to their sparse reward and long decision horizon nature. However, in many navigation tasks, high-level (HL) task representations, like a rough floor plan, are available. Previous work has demonstrated efficient learning by hierarchal approaches consisting of path planning in the HL representation and using sub-goal...
