Abstract
In allusion to the existing low recognition rate and robustness problem in obstacle detection; a simple but effective obstacle detection algorithm of information fusion in the depth and infrared is put forward. The scenario is segmented by the mean-shift algorithm and the pixel gradient of foreground is calculated. After pretreatment of edge detection and morphological operation, the depth information and infrared information are fused. The characteristics of depth map and infrared image in edge detection are used for the raised method, the false rate of detection is reduced, and detection precision is improved. Since the depth map and infrared image are not affected by natural sunlight, the influence on obstacle recognition due to the factors such as light intensity and shadow is effectively reduced and the robustness of the algorithm is also improved. Experiments indicate that the detection algorithm of information fusion can accurately identify the small obstacle in the view and the accuracy of obstacle recognition will not be affected by light. Hence, this method has great significance for mobile robot or intelligent vehicles on obstacle detection in outdoor environment.
Highlights
Detection of the obstacle has a wide application in smart robots, intelligent vehicles, and autonomous agricultural vehicles
The sensors used for traditional obstacle detection mainly include laser radar sensors, ultrasonic sensors, infrared sensors, and visual equipment [3]
Intelligent vehicle named Stanley [5] from Stanford University installs a lot of laser radar sensors at the top of the car, which is used for judging whether the area is an obstacle or an area that can be passed through by 2D grid based on Markov model and height difference between adjacent points
Summary
Detection of the obstacle has a wide application in smart robots, intelligent vehicles, and autonomous agricultural vehicles. The sensors used for traditional obstacle detection mainly include laser radar sensors, ultrasonic sensors, infrared sensors, and visual equipment [3]. Hua et al [7] proposed a method to detect phase position by modulating double-sideband amplitude, in which excitation signal of ultrasonic pulse was modulated by using a low frequency signal and adopting appropriate modulation data. This method guarantees the resolution of the phase detection obstacle, and expands the scope of the obstacle detection to a certain extent. Infrared thermal imaging system has a certain ability to penetrate and it can distinguish
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