Person tracking and following with 2D laser scanners

Abstract

Having accurate knowledge of the positions of people around a robot provides rich, objective and quantitative data that can be highly useful for a wide range of tasks, including autonomous person following. The primary objective of this research is to promote the development of robust, repeatable and transferable software for robots that can automatically detect, track and follow people in their environment. The work is strongly motivated by the need for such functionality onboard an intelligent power wheelchair robot designed to assist people with mobility impairments. In this paper we propose a new algorithm for robust detection, tracking and following from laser data. We show that the approach is effective in various environments, both indoor and outdoor, and on different robot platforms (the intelligent power wheelchair and a Clearpath Husky). The method has been implemented in the Robot Operating System (ROS) framework and will be publicly released as a ROS package. We also describe and will release several datasets designed to promote the standardized evaluation of similar algorithms.