A Framework for Socially Aware Navigation Based on Robocentric Perception of People Social Cues

Autor: Manoel Andrade, José Diaz-Amado, Raphaell Sousa, Dennis Barrios-Aranibar, Fábio Leite, Daniel Almeida, Gabriel Alves
Rok vydání: 2022
DOI: 10.3233/aise220016
Popis: In the last few years, the application of robotics in environments common to human beings has been increasing. There exists several proposals of socially aware navigation frameworks for mobile robots, however all of them generally focused in a specific aspect of social relantionships between humans and robots; so, there exist a lack of approaches that integrate all the aspects related to social navigation. This work aims to propose an autonomous navigation framework based on the integration of social perception elements (from a robocentric perspective) with proxemics modelling, considering the presence of human beings and the perception of their needs, feelings or intentions. We verified the feasibility of our approach by implementing it in ROS and Gazebo, and making a qualitative evaluation of its performance in two simulated scenarios where we included people with different fellings about robot prescence, that triggered changes in the path planned by the robot in real time. So, it was concluded that this framework is feasible for implementing social navigation in mobile robots.
Databáze: OpenAIRE