What Is Visual Navigation?

In the field of navigation, mechanical vision navigation and laser navigation are two major autonomous positioning technologies. Together with satellite navigation (GNSS) and inertial navigation (INS), they form the positioning solutions for intelligent systems.

The implementation process of mechanical vision navigation

Build an appropriate image imaging system to collect target images. The collected sample images are preprocessed by using image processing technology to enhance the image quality. The target object is segmented from the image background and the feature information is extracted by using the relevant feature calculation method to obtain the feature vector composed of feature parameters with strong representational capabilities such as color, shape and texture of the target object. To avoid excessive redundant information imposing a large amount of computational load on the system and affecting the recognition accuracy and efficiency of the system, the obtained feature vectors are screened and optimized. Select an appropriate classifier for training and provide the recognition results. The image processing effect, selected features and the design of the classifier in this process directly determine the recognition effect of the system and are the core of machine vision technology.

1. Image processing technology is relatively mature. The common image preprocessing process is: grayscale conversion → geometric transformation (cropping, translation, rotation, etc.)→ image enhancement (filtering, smoothing, sharpening, etc.).

2. Target segmentation methods include threshold segmentation methods (global threshold, local Min value, Otsu), region segmentation methods, watershed segmentation methods, and K-means clustering segmentation, etc.

3. Feature extraction methods include color (color moment, color set, color histogram, color aggregation vector, etc.), texture (gray-level co-occurrence matrix method, geometric method, model method, wavelet transform, etc.), shape (Fourier transform, Hough transform, area, perimeter, rectangularity, quasi-roundness, minimum external rectangle aspect ratio, Hu invariant moment, etc.), spatial relationship, etc.

4. Feature selection and optimization methods include Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Multidimensional Scaling (MDS), flow pattern learning, etc.

5. In recognition and classification methods, traditional statistical pattern recognition methods include Support Vector Machine (SVM), Bayesian, discriminant function, etc. With the development of Machine Learning (ML) technology and the application of methods such as artificial neural networks (ANN), genetic algorithms, clustering algorithms, and transfer learning, the recognition accuracy and stability of machine vision systems have been significantly improved.

Mechanical vision navigation often needs to complement other technologies to form an all-domain positioning capability. Inertial navigation systems (INS) use sensors such as accelerometers and gyroscopes to measure the motion state of objects, thereby calculating their position and direction. Satellite navigation technologies such as GPS, GLONASS, Galileo, and Beidou achieve positioning and navigation by sending signals through satellites and receiving them with ground receivers.

Jinan Keya Electron Science And Technology Co.,Ltd. Developed high precision auto steering motor support AGOPENGPS. The AgOpenGPS autosteer motor, together with the controller, tablet, steering wheel, front wheel sensor, GNSS antenna, etc. constitutes the auto steering system. Satellite antennas can simultaneously receive signals from GPS, Galileo, GLONASS and the Beidou satellite system. Centimeter-level positioning is achieved by using RTK high-precision satellite positioning technology. Meanwhile, the auto steering system supports technologies such as inertial navigation, automatic control, and electric steering, and controls the steering wheel to guide agricultural machinery to operate automatically along the prescribed route.

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