Ecological Approach for Object Relationship Extraction in Elderly Care Robot
Adnan Rachmat Anom Besari, Wei Hong Chin, Naoyuki Kubota, Kurnianingsih Kurnianingsih · 2020
This paper proposes an ecological approach for object relationship extraction. First, we explain the ecological approach used to develop our previous works in the perception of a partner robot. Second, we developed a framework for finding the relation of objects based on scenarios of daily human activities. We represent the relationships among objects in a graph consisting of nodes and edges. Graph Convolutional Networks (GCN) is used to train the graph and perform semi-supervised classification. Third, we generate and prepare the datasets and then train the GCN. Finally, we present training visualization in two different scenarios. The proposed methods allow the system to identify the object based on its relationship. This approach is then used as a starting point to implement the ecological factors in elderly care robot applications.