ATV Navigation in Complex and Unstructured Environment Containing Stairs

Abstract

Self-driving and robotic technologies have been widely used in recent years. However, before L5 autonomy has been mature, it is more important and meaningful to apply these technologies to some wheeled robots on specific scenes. All-terrain vehicles (ATV) are widely used in urban search and rescue. An unstructured complex scene on which an ATV works usually contains many unusual obstacles, such as stairs. As a result, it is important for autonomous ATVs to detect, localize, and traverse stairs. In this paper, a real-time outdoor stair detection and localization method is proposed. A VLP-16 LIDAR is used to collect environment data, and the stairs are detected and localized using a single frame of LIDAR data by their geometric features, such as slope and parallel edges. A stair navigation strategy is also proposed in this paper. 3-axis attitudes measured by IMU are used during stair climbing on the basis of the coupling between roll and yaw on a slope. Experiments are carried out and the results prove the robustness and accuracy of detection and localization algorithm. The navigation strategy is proven to be safe and feasible.