| Researches on agricultural robot and their vision navigation systems are attracting more and more attentions and becoming an important direction of exploring application of high technology (intelligent control) in agricultural machines and equipments. Agricultural environment is complicated, open and unstructured. How to extract visual information of navigation is a difficulty of vision navigation. Illumination variation makes extracting algorithms of guidance parameters unstable and existence of shadows furthermore interferences image processing and analysis. So some new algorithms of removing illumination influence should be explored to improve stability of vision navigation system. Human visual system has property of color constancy. How to introduce human color constancy into machine vision is a train of thought of solving illumination problem.In the thesis, to realize autonomous navigation of agricultural robot in the field, illumination influence problem in vision navigation system was studied firstly with color constancy theories, a moblie robot platform for agriculture was designed, vision navigation system was constructed, and trials of crop line guidance and headland turn were carried through. Main research contents and conclusions include:(1) Light microscopic influence on images was investigated through image fomation process. Theory of color constancy was introduced to solve illumination influence problem, and its current status was reviewed, two color constancy ways of solving illumination influence problem were concluded. One way is to take the conversion of images from in the non-canonical illumination to in the canonical illumination. Another way is to obtain illumination invariants.(2) Some color constancy algorithms, which to take the conversion of images from in the non-canonical illumination to canonical illumination, were tested. These algorithms estimate illumination color globally and locally according to statistical information of image data, and then obtain color-corrected canonical images by von Kries model. A color learn based color image processing algorithm was proposed, Statistical results of image segmentation experiments to original images and canonical images showed, illumination variation influenced image segmentation quality, but canonical images under canonical illumination could improve segmentation results. Finally, according to time cost and segmentation effects, gray world algorithm and three local illumination estimation algorithm is equivalent in segmentation results, but gray world algorithm is high in efficiency and fit for real-time vision navigation, so gray world algorithm to obtain canonical image is chosen in later vision navigation system.(3) Shadow formation process was analyzed. Theory of illumination invariant image was described. Based on this, a method of shadow removal was derived. To obtain the illumination invariant image, a camera-dependent illumination invariant angle should be measured. Aiming at solving this problem inconvenient, a method of minimal entropy was introduced. Results showed that method of shadow removal based on illumination invariant image could remove shadows efficiently. An enhanced OSTU threshold method was proposed to segment the illumination invariant image, and perfect effects were obtained.(4) Based on founded model of farmland navigation working environment, navigation process of agricultural robot in the field was planed and main steps of navigation parameters extraction were analysised. An optimized Hough transform algorithm was proposed to extract guidance parameters for only single crop row. A line-scan algorithm with least squares theory was proposed to extract guidance parameters for double crop rows. A horizontal projection algorithm was used to detect headland. Tests of these image processing algorithms showed, all the algorithms were reasonable and reliable and total time cost of vision algorithms was enough for vision navigation.(5) A CAN-based distributed control technology was introduced. A 4WD and 4WS robot platform was designed. A monocular vision navigation system was constructed. Multi-thread based vision navigation system software was developed. Validity and reliability of former vision algorithms were verified in the mobile robot platform. Results from cropline tracking tests showed that outdoor vision navigation system was feasible. In the end, an optical-encoder-based Dead Reckoning algorithm was proposed to fulfill headland turn function, and simulated tests showed the algorithm could suffice for headland turn. |
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