Robust Cooperative Target Detection for a Vision-Based UAVs Autonomous Aerial Refueling Platform via the Contrast Sensitivity Mechanism of Eagle's Eye

In this paper, a robust cooperative target detection method inspired by contrast sensitivity mechanism of eagle's eye is proposed to extract the cooperative target, aiming at reducing the computation load and improving the accuracy of feature extraction. The contrast sensitivity mechanism is simulated based on the attenuation effect of CSF of an eagle to suppress the texture edges. The comparison experimental results compared with the Canny edge detection operator demonstrated the excellent performance of our proposed method in extracting salient contours and suppressing texture edges. Besides, a binocular vision based AAR platform for UAV is designed and implemented in this paper. Applying our proposed detection method to a series of outdoor experiment images captured from two challenging lighting conditions, the cooperative targets are successfully extracted while the other disturbance areas are removed dramatically. The outdoor flight tests are conducted to verify the visual measurement system and the hardware platform. The experimental results verified the feasibility and effectiveness of our developed visual measurement algorithms. In the future, we will focus on the influence of other factors on the marker detection to further improve the accuracy of marker detection, like illumination, the image quality influenced by the motion of tanker UAV.