Performance Evaluation Methods for Human Detection and Tracking Systems for Robotic Applications

Abstract

Detecting and tracking people is becoming more important in robotic applications because of the increasing demand for collaborative work in which people interact closely with and in the same workspace as robots. New safety standards allow people to work next to robots but require that they be protected from harm while they do so. Sensors that detect and track people are a natural way of implementing the necessary safety monitoring and have the added advantage that the information about where the people are and where they are going can be fed back into the application and used to give the robot greater situational awareness. This report describes work on defining and testing performance evaluation measures that provide quantitative information about how well a human detection and tracking system performs. The results should help users determine if such a system will provide sufficient protection for people to be able to work safely in collaborative applications with industrial robots.