Today, social robotics encompasses the ability to improve robot communication with humans. In this aspect, the robot’s behaviors are extended to maintain an acceptable human-robot interaction (HRI) for people, which implies that the robot must know the environment in which it is located and establish rules of behavior. Likewise, a large part of the robot’s capabilities is concentrated in the planning of social paths influenced by the emotions of the human being. In which, the robot is able to vary the speed of the path or learn where it should be located and where it should not be. In this article, a new cost function for A* path planning method is proposed for social navigation, on an environment shared with people with different emotional characteristics. These characteristics are classified into three categories of emotions (positive, neutral and negative). Demonstrating the results and advantages of the proposed algorithm in simulated virtual environments with crowds of people interacting.
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