Abstract
Being aimed at the obstacle recognition problem of unmanned ground vehicles in cross-country environment, this paper uses monocular vision sensor to realize the obstacle recognition of typical obstacles. Firstly, median filtering algorithm is applied during image preprocessing that can eliminate the noise. Secondly, image segmentation method based on the Fisher criterion function is used to segment the region of interest. Then, morphological method is used to process the segmented image, which is preparing for the subsequent analysis. The next step is to extract the color featureS, color featureaand edge feature “verticality” of image are extracted based on the HSI color space, the Lab color space, and two value images. Finally multifeature fusion algorithm based on Bayes classification theory is used for obstacle recognition. Test results show that the algorithm has good robustness and accuracy.
Highlights
Unmanned ground vehicle has been a research hotspot, and it has broad application prospect in military, civil, scientific research, and other fields [1]
Mnaduchi et al put forward an obstacle detection method, using the disparity map based on stereo vision, and test results proved that the method has better robust [3]
Huihai et al combined machine vision and ultrasonic sensors to detect obstacles, and test results show that the obstacle detection algorithm is effective and practical [6]
Summary
Unmanned ground vehicle has been a research hotspot, and it has broad application prospect in military, civil, scientific research, and other fields [1]. For the obstacle detection and recognition of UGV in cross-country environment, domestic and foreign researchers have done a lot of research. Yanmin et al proposed an obstacle detection algorithm based on stereo vision and laser radar, which can separate the high grass and other obstacles (such as trunks and stones) [7]. The main work of this paper is to research obstacle detection and recognition technology based on monocular vision in cross-country environment. Chapter 1: Chapter 1 includes an introduction; it introduces the research status of unmanned vehicle obstacle detection and recognition technology, the meaning and main contents of this paper. Chapter 2: obstacle detection is included in Chapter 2 that introduces an obstacle detection method based on monocular visual images, including image preprocessing, image segmentation, and morphological image processing.
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