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Performance Evaluation of Human Detection Systems for Robot Safety



William P. Shackleford, Geraldine S. Cheok, Tsai H. Hong, Kamel S. Saidi, Michael O. Shneier


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 paper 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 safely able to work in collaborative applications with industrial robots.
Journal of Intelligent & Robotic Systems


Human detection, human-robot collaboration, human tracking, performance evaluation, performance metrics, robot safety
Created January 22, 2016, Updated November 10, 2018