Learning Relationships Between Objects and Places by Multimodal Spatial Concept with Bag of Objects

Shota Isobe, Akira Taniguchi, Yoshinobu Hagiwara, Tadahiro Taniguchi

Abstract: Human support robots need to learn the relationships between objects and places to provide services such as cleaning rooms and locating objects through linguistic communications. In this paper, we propose a Bayesian probabilistic model that can automatically model and estimate the probability of objects existing in each place using a multimodal spatial concept based on the co-occurrence of objects. In our experiments, we evaluated the estimation results for objects by using a word to express their places. Furthermore, we showed that the robot could perform tasks involving cleaning up objects, as an example of the usage of the method. We showed that the robot correctly learned the relationships between objects and places.