Path Planning Method of Self-Propelled Bridge Inspection Vehicle based on Support Vector Machine

Abstract

Present, there is a high rate of missing inspection in the path planning method of bridge inspection vehicle, and the planning path is repeated, which affects the detection efficiency. In order to overcome the above technical deficiencies, a self-propelled bridge inspection vehicle path planning method based on support vector machine is designed. Through the sample training based on support vector machine, the maximum interval method is used to partition the hyperplane to reduce the collision of obstacles. The grid method is used to construct the environment model of the bridge to determine the specifications of the grid. Each grid is given different values and meanings to represent different environmental information. Finally, the path planning of the operation vehicle is realized. In the experiment, two methods are used to plan the path of a bridge inspection project, and the two paths obtained from the plan are evaluated. The experimental results show that the path of the inspection vehicle obtained by the designed path planning method can achieve all-round coverage of the bridge inspection. And there is no path duplication, which verifies the effectiveness of the design method.