A State Representation Model for Robots Unaffected by Environmental Changes

摘要

To interact with the external environment, robots represent it as a state using sensor data. In this study, we present a state representation based on noisy sensor data using distances among probability distributions. Our proposed representation is not influenced by environmental changes, that is, sensor signals maintain an identical state even after certain environmental changes. We represent sensor signals as probability distributions and the distances between such distributions express a state. To confirm the effectiveness of our proposed state representation, we conducted experiments using a mobile robot with distance sensors. Experimental results confirmed that our proposed representation correctly recognizes similar states using a converted sensor signal.