HRL4IN: Hierarchical Reinforcement Learning for Interactive Navigation with Mobile Manipulators

Understand

Most common navigation tasks in human environments require auxiliary arm interactions, e.g.

• opening doors, pressing buttons and pushing obstacles away.
• This type of navigation tasks, which we call Interactive Navigation, requires the use of mobile manipulators: mobile bases with manipulation capabilities.
• Interactive Navigation tasks are usually long-horizon and composed of heterogeneous phases of pure navigation, pure manipulation, and their combination.