The Hands-Free Push-Cart: Autonomous Following in Front by Predicting User Trajectory Around Obstacles

Abstract

This paper demonstrates an autonomous mobile robot that follows a walking user while staying ahead of them. Despite several useful applications for autonomous push-carts, this problem has received much less attention than the easier problem of following from behind. In contrast to previous work, we use multi-modal person detection and a human-motion model that considers obstacles to predict the future path of the user. We implement the system with a modular architecture of obstacle mapper, human tracker, human motion model, robot motion planner and robot motion controller. We report on the performance of the robot in real-world experiments. We believe that approaches to this largely overlooked problem could be useful in real industrial, domestic and entertainment applications in the near future.