ass日本风韵熟妇pics男人扒开女人屁屁桶到爽|扒开胸露出奶头亲吻视频|邻居少妇的诱惑|人人妻在线播放|日日摸夜夜摸狠狠摸婷婷|制服 丝袜 人妻|激情熟妇中文字幕|看黄色欧美特一级|日本av人妻系列|高潮对白av,丰满岳妇乱熟妇之荡,日本丰满熟妇乱又伦,日韩欧美一区二区三区在线

Aiming at the visual navigation system works in the orchard environment, a visual navigation method based on U-Net for path recognition was proposed. Labelme was used to label the road mask in the collected images and made the orchard dataset. Based on data enhancement, the convolutional neural network was trained to obtain the orchard road segmentation model which could identify the road region. The road segmentation mask was used to get navigation information and generate keypoints for path fitting. Using the midpoints as control points, the navigation path was recognized by multi-segment cubic B-spline curve fitting method. Experiments of semantic segmentation and path recognition were carried out respectively, when the critical threshold is 0.4, the results showed that IoU of semantic segmentation model in weak light, ordinary light, and strong light was 89.52%, 86.45% and 86.16%, respectively. The method of edge information extraction and path recognition could adapt to various visual angles of the road mask and get a smooth navigation path. Under different illumination and visual angle conditions, the average pixel error was 9.5 pixel, and the average distance error was 0.044m. It was known that the width of the road was about 3.1m, so the average distance error ratio was 1.4%. The normal speed of the tracked vehicle in the orchard was mostly 0~1.4m/s, and the average processing time of a single field image was 0.154s. Under the current orchard environment and hardware configuration, it was proved that this method had a good performance in accuracy and real-time. This research can provide an effective reference for visual navigation task in the orchard environment.