Autonomous Drone-Ground Robot Alignment Through Ground Robot Visual Servo Control With Drone Detection and Tilt Correction

Abstract

Retrieving ground robots from dangerous environments after their operation is a challenging task that poses risks for the personnel. Some researchers often employ drones for retrieval, which makes operations safer. However, this set-up requires an accurate method that guarantees drone and ground robot alignment due to inaccuracies in standard GPS devices, drone drifts, and wind gusts. Hence, this research article introduces simultaneous object detection and tilt correction as part of visual servoing to achieve precise drone-rover alignment. Drone detection using YOLOv8 and a tilt correction algorithm was integrated for the proposed visual servo of the ground robot. The study collected 3024 images as a data set for drone detection. The experimental results show that the trained instance segmentation model detected and captured drone objects. The study conducted an initial test for visual servo control of the ground robot in various surface terrains, resulting in a maximum alignment error on rough surfaces. Furthermore, the study conducted drone-ground robot alignment real test in an outdoor field setting. The alignment between the drone and the ground robot produced a maximum alignment error of 20.3 cm, below the threshold error. The open field experiments verified the effectiveness of the ground robot's visual servo control with an actual drone operation.