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Mobile robotics as a branch in the field of robotics research in recent years a wide range of development and application of, for example, have widely used in various fields of the space probe, military explosion-proof robot, civilian home service robots. Complete autonomous mobile robot system design issues need to be resolved first: how to use their own portable sensor device, and aware of their surroundings, self-planned path to avoid foreign bodies collide. Basic research, such as the main content of this paper is focused on mobile robot path planning and control strategies based mobile robot vision system control strategy, the path planning algorithm based on fuzzy control methods and artificial potential field model. This article details are as follows: 1, in-depth analysis of the theory and technology of the mobile robot, including the structure of the mobile robot platform, sensor devices, the underlying drive structure mobile robot dynamics model. 2, in-depth study of the theoretical knowledge of the machine vision, comprehensive analysis and panoramic vision system, including the panoramic system hardware structure, panoramic imaging principle. 3, a mobile robot navigation control strategy based on panoramic vision technology. This paper presents a measurement principle of similar triangles, to complete the feature information extracted from the two-dimensional images taken by the panoramic vision equipment, to measure the actual distance of the target with the robot in a three-dimensional scene, the method is simple and practical, real-time, be able to meet the needs of the mobile robot to determine the real-time requirements of the target. 4, the mobile robot path planning using common methods, this paper, a fuzzy control method for mobile robot path planning. Path planning methods, the use of traditional fuzzy control mobile robots corners in some environments, there is a lack of paper, take the safe route since adjusting fuzzy control improvements to make up for the traditional fuzzy control method deficiencies Office. 5, path planning method based on artificial potential field model for the traditional artificial potential field path planning the local extreme cases, this paper presents an improved potential field model. The model draws on the penalty function method can effectively deal with optimization function model constraints problems, first of all to the artificial potential field path planning model into the optimization problem in the problem space, re-introduction of the penalty function method to deal with the local minimum problem, and finally Simulation results verify and achieved good results.
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