4.6 Article

Distance Measurement of Unmanned Aerial Vehicles Using Vision-Based Systems in Unknown Environments

期刊

ELECTRONICS
卷 10, 期 14, 页码 -

出版社

MDPI
DOI: 10.3390/electronics10141647

关键词

distance measurement; localization; mapping; robotics; segmentation; UAV; vision-based

资金

  1. AGH University of Science and Technology [16.16.120.773]

向作者/读者索取更多资源

This paper proposes a novel framework for indoor positioning of unmanned aerial vehicles (UAV) using a camera, achieving an accuracy of 91.7% and a computation time of 8 frames per second (fps).
Localization for the indoor aerial robot remains a challenging issue because global positioning system (GPS) signals often cannot reach several buildings. In previous studies, navigation of mobile robots without the GPS required the registration of building maps beforehand. This paper proposes a novel framework for addressing indoor positioning for unmanned aerial vehicles (UAV) in unknown environments using a camera. First, the UAV attitude is estimated to determine whether the robot is moving forward. Then, the camera position is estimated based on optical flow and the Kalman filter. Semantic segmentation using deep learning is carried out to get the position of the wall in front of the robot. The UAV distance is measured using the comparison of the image size ratio based on the corresponding feature points between the current and the reference of the wall images. The UAV is equipped with ultrasonic sensors to measure the distance of the UAV from the surrounded wall. The ground station receives information from the UAV to show the obstacles around the UAV and its current location. The algorithm is verified by capture the images with distance information and compared with the current image and UAV position. The experimental results show that the proposed method achieves an accuracy of 91.7% and a computation time of 8 frames per second (fps).

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据