Learning to Behave in Space: a Qualitative Spatial Representation for Robot Navigation with Reinforcement Learning

ion mechanism to create a representation of space consisting of the circular order of detected landmarks and the relative position of walls towards the agent's moving direction. The use of this representation does not only empower the agent to learn a certain goal-directed navigation strategy faster compared to metrical representations, but also facilitates reusing structural knowledge of the world at different locations within the same environment. Acquired policies are also applicable in scenarios with different metrics and corridor angles. Furthermore, gained structural knowledge can be separated, leading to a generally sensible navigation behavior that can be transferred to environments lacking landmark information and/or totally unknown environments.

• Type: Journal
• Year: 2008
• Where: IJAIT
• Authors: Lutz Frommberger
• Keywords: Certain Goal-directed Navigation, IJAIT 2008, Ion Mechanism, Structural Knowledge