Abstract:

Robots need to understand the human social behaviors to interact with human correctly and to service for people in public and home environments. The way in which robots are going to live with humans has become an important issue. Therefore, estimation and prediction of dynamic human society environment are very important for robot. Standing in line is one of the most common human social behaviors and robot needs to learn it.

The imminent trend for our society would be personalization of robots capable of offering services that cater to individual needs. In order to provide a more convenient way of life, the robots are able to download the 3-Dimensional models supplied by the respective apparel stores upon arrival at the entrance. In addition, codes are immediately processed so that their owners could fit the clothes efficiently. Furthermore, apart from their basic functions of replacing their owners in errands such as purchasing goods and paying the bill, they understand the importance of human interactions during the process of queuing. This paper includes the use of probability in analyzing the model of queuing under a dynamic environment. Other than that, this paper also offered formulas in detecting and predicting the situation of queues. Nevertheless, methods of using only cameras to capture and track the customer in front and react to difference of image are also part of the paper.