Abstract-Service robots need to be able to recognize and identify objects located within complex backgrounds. Since no single method may work in every situation, several methods need to be combined. However, there are several cases when autonomous recognition methods fail. We propose an interactive recognition method in these cases. To develop a natural Human Robot Interaction (HRI), it is necessary that the robot should unambiguously perceive the description of an object given by human. This paper reports on our experiment in which we examined the expressions humans use in describing ordinary objects. The results show that humans typically describe objects using one of multiple colors. The color is usually either that of the object background or that of the largest object portion. Based on these results, we describe our development of a robot vision system that can recognize objects when a user adopts simple expressions to describe the objects. This research suggests the importance of connecting 'symbolic expressions' with the 'real world' in human-robot interaction.

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Service robots need to be able to recognize objects located in complex environments. Although there has been recent progress in this area, it remains difficult for autonomous vision systems to recognize objects in natural conditions. In this paper, we propose an interactive object recognition system. In this system, the robot asks the user to verbally provide information about an object that it cannot detect. In particular, it asks the user questions regarding color and spatial relationship between objects depending on the situation. Experimental results confirm the usefulness and efficiency of our interaction system.

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Service robots need to be able to recognize and identify objects located within complex backgrounds. Since no single method may work in every situation, several methods need to be combined. However, there are several cases when autonomous recognition methods fail. We propose several types of interactive recognition methods in those cases. Each one takes place at the failures of autonomous methods in different situations. We proposed four types of interactive methods such that robot may know the current situation and initiate the appropriate interaction with the user. Moreover we propose the grammar and sentence patterns for the instructions used by the user. We also propose an interactive learning process which can be used to learn or improve an object model through failures.