Active Learning on Service Providing Model: Adjustment of Robot Behaviors Through Human Feedback

As robots are put into humans' daily life, the assigned tasks to robots are varied, and the different needs of people interacting with robots are immense. As a result, when facing different users, it is important for robots to personalize the interactions and provide user-desired services. This paper, therefore, proposes a learning strategy on the service-providing model. Through human feedback, the strategy enables the robot to learn the users' needs, as well as preferences, and adjust its behaviors. Here, we assume that users' needs and preferences may vary with time; hence the goal of this paper is to let the adjustment of robot behaviors be able to adapt to those variations. In turn, the service-providing model of the robot could adjust online as well. That is, it can select a new action from those favorable actions that have already been selected or an action that is not an unfavorable action but has annoyed humans recently. To implement our system, the service robot under discussion is applied to the home environment. For performance evaluation, we have performed extensive experiments that satisfactorily demonstrate that our robot can provide services to different users and adapt to their preference change.

I. Introduction

Human–robot interaction (HRI) [1] has emerged as a research field that is dedicated to understanding, designing, and evaluating robotic systems for use by or with humans. While multimodal channels and sensor fusion allow for more robust communications between them, study on how to improve the natural HRI is still undergoing. The result on human acceptance of the robot [26] can be deemed as a preliminary pioneer that may be helpful to developing natural communication interfaces. After shifting from a robot-centered point of view, more and more researchers have been drawn to study the interactions and reciprocal effects between robots and humans. A new generation of robots is expected to adapt to users, to interact with them naturally, and to participate in their daily lives. One important perspective is that robots should interact with humans in their most natural ways.