The task selection mechanism for interactive robots: Application to the intelligent life supporting system

The essential challenge in the future ubiquitous networks is to make information available to people not only at any time, at any place, and in any form, but with the right thing at the right time in the right way by inferring the users' situations. Several psychological experiments show that there are some associations between each user's situations including the user's emotions and each user's task selection. Utilizing those results, this article presents a situation-based task selection mechanism that enables a life-supporting robot system to perform tasks based on the user's situation. Stimulated by interactions between the robot and the user, this mechanism constructs and updates the association between the user's situation and tasks so that the robot can adapt to the user's behaviors related to the robot's tasks effectively. For the user adaptation, Radial Basis Function Networks (RBFNs) and associative learning algorithms are used. The proposed mechanism is applied to the CRF3 (Character robot face 3) system to prove its feasibility and effectiveness.