Modified social force model with face pose for human collision avoidance

摘要

In order for robots to be a part of human society, their social accceptance is an important issue if smooth interaction with humans is to be achieved. We propose a modified social force model that allows robots to move naturally like humans, based on estimated human motion and face pose. We add to the previous model the effect of the force due to face pose, in order to predict human motion and compute the robot motion itself. Our approach was implemented and tested on a real humanoid robot in a situation in which a human is confronted with a robot in an indoor environment. Experimental results illustrate that the robot is able to perform human-like navigation by avoiding the human in a face-to-face confrontation. Our system provides accurate face pose tracking that allows a robot to have a more realistic behaviour compared to the original social force model.