A hierarchical approach for updating targeted person states in human-following mobile robots

In the human-following task, the human detection, tracking and identification are fundamental steps to help the mobile robot to follow and maintain an appropriate distance and orientation to the selected target person (STP) without any threatenings. Recently, along with the widespread development of robots in general and service robots in particular, not only the safety, but the flexibility, the naturality and the sociality in applications of human-friendly services and collaborative tasks are also increasingly demanded with a higher level. This request poses more challenges in robustly detecting, tracking and identifying the STP since the human–robot cooperation is more complex and unpredictable. Obviously, the safe natural robot behavior cannot be ensured if the STP is lost or the robot misidentified its target. In this paper, a hierarchical approach is presented to update the states of the STP more robustly during the human-following task. This method is proposed with the goal of achieving good performance (robust, accurate and fast response) to serve safe natural robot behaviors, with modest hardware. The proposed system is verified by a set of experiments, and shown reasonable results. Graphical abstract: [Figure not available: see fulltext.]