Construction of Human Behavior Cognitive Map for Robots

Abstract

With the advancement of robotics, the importance of service robots in society is increasing. It is crucial for service robots to understand their environment so that they can offer suitable responses to humans. To realize the use of space, robots primarily use an environment model. This paper is focused on the development of an environment model based on human behaviors. In this model, a new neural network structure called dynamic highway networks is applied to recognize humans’ behaviors. In addition, a two-dimensional pose estimator, Laban movement analysis, and the fuzzy integral are employed. With these methods, two new behavior-recognition algorithms are developed, and a method to record the relationship between behavior and environment is proposed. Based on the proposed environmental model, robots can identify abnormal behavior, provide an appropriate response and guide a person toward the desired normal behavior by identifying abnormal behavior. Simulations and experiments justify the proposed method with satisfactory results.