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Aiming at the problem of bad working environment of bulldozer in landfill, this paper presents a target detection method suitable for autonomous working bulldozer. Firstly, the working environment information was obtained by the binocular camera, the maximum inter-class variance method was used to remove the sky background by binarization of the image, and the color component of the ground was extracted from the HSV color space and converted into a binarization image. The absolute value of the difference between the two binarization images was the approximate area of the working target. Then the binocular camera was calibrated and the feature points were detected and matched in the target area. The parallax was obtained by triangulation principle to obtain the depth information of the target. The experimental results show that the method can correctly extract the depth information of the target area and target, and the accuracy is high, which can meet the requirements of the bulldozer in the landfill for target detection.

In order to solve the automatic transportation of heavy materials under the limited working space of production workshops and warehouses, two sets of heavy-duty omnidirectional mobile robot motion control systems with steering wheel drive units were designed. The steering wheel combination drive unit of the “walking + steering” set is used to build the mobile robot chassis, and the mechatronics servo system and mathematical model of multi-motor coordinated motion are constructed. The communication between the controller and the steering wheel combination drive unit is established through the CAN bus. The specific implementation is to capture and analyze the control signal through the controller to obtain the desired motion mode, to obtain the motion of each set of steering wheel unit through the mathematical model, and to realize the desired motion through the synthesis of each set of steering wheel unit motion. It has been verified by experiments that the two sets of steering wheel unit-driven mobile robot control system realizes the zero turning radius, 360-degree omnidirectional movement of the robot and rotation during the movement. It can be used for flexible work in tight spaces.

In order to realize the identification and positioning of the working object when the excavator works independently, it is necessary to calibrate the binocular camera to determine that the binocular is the internal and external parameters of the camera. This paper focuses on the calibration of binocular camera, and determines the transformation relationship among world coordinate system, camera coordinate system and image coordinate system based on binocular stereo vision ranging principle. The checkerboard images that meet the calibration requirements are selected by using the visual toolbox of MATLAB. The camera calibration process is carried out to determine the camera parameters to be determined. The calibration parameters are analyzed and compared to preliminarily verify the accuracy of the calibration parameters. Finally, the error source is analyzed in QT5.14.2 programming environment combined with OpenCV3.4.10, the calibration method meets the application requirements.

Aiming to the difficulty of micro pressure detection and the difficulty of micro flow control in the testing process of hydrocephalus shunt, the principle of the shunt performance detection was analyzed.In this study, the author analyzed the principle of several items of shunt performance detection,and used advanced micro pressure sensor and micro flow peristaltic pump to overcome the micro pressure detection and micro flow control technology.At the same time,This study also puted many common experimental projects integrated, and successfully developed the automatic detection system for a shunt performance detection function, to achieve a test with high precision, high efficiency and automation.