Research on a UAV fine descent system based on improved YOLOv4-tiny

Tianli Liu; Tao Wang; Chunfei Li; Yue Liu; Changming Zhou; Jian Wu

doi:10.1117/12.2652190

10 November 2022 Research on a UAV fine descent system based on improved YOLOv4-tiny

Tianli Liu, Tao Wang, Chunfei Li, Yue Liu, Changming Zhou, Jian Wu

Proceedings Volume 12331, International Conference on Mechanisms and Robotics (ICMAR 2022); 123310M (2022) https://doi.org/10.1117/12.2652190
Event: International Conference on Mechanisms and Robotics (ICMAR 2022), 2022, Zhuhai, China

Abstract

The application scope of UAV in the power field is gradually expanding, which puts forward higher requirements for the accurate landing of UAV. At this stage, the fixed-point landing of UAV mainly depends on RTK, but RTK is easy to be disturbed by the external environment, so it can not meet the requirements of fine landing. This paper proposes an improved yolov4-tiny algorithm, which adds the convolutional attention module to the yolov4-tiny network structure feature pyramid to reduce the interference of complex backgrounds on target recognition. In this system, the UAV is guided to fly above the nest by RTK in the first, and then the landing code is recognized by improved yolov4 tiny algorithm, so as to realize the accurate landing of UAV. Through the field fine landing test of UAV, it is found that the landing accuracy of the proposed technology is high and meets the landing requirements.

Citation Download Citation

Tianli Liu, Tao Wang, Chunfei Li, Yue Liu, Changming Zhou, and Jian Wu "Research on a UAV fine descent system based on improved YOLOv4-tiny", Proc. SPIE 12331, International Conference on Mechanisms and Robotics (ICMAR 2022), 123310M (10 November 2022); https://doi.org/10.1117/12.2652190

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