Person-following using fuzzy inference

Abstract

For a service robot, being able to follow a person to do a required task is a must have skill. Such an ability, however simple in concept, has some requirements to be met which makes a simplistic direct implementation unsatisfactory. Most notably, the robot following the human has to keep at a certain safe distance from the person and at the same time move in a smooth manner which does not appear threatening to the person. Also, such a smooth movement would potentially prolong the lifetime of the robot's locomotive system. In this paper, we propose using fuzzy inference as the decision system achieving smoothness and person-following behavior while keeping a safe distance from that person. The system was tested using a laser range finder to detect a person's legs giving the inference system a distance and a direction to go to. The experimental results showed that even though the detection of legs was subject to noise and false negatives, the robot still achieved the goals of smoothness of motion, keeping of a safe distance, and of course, following its target.