Research On The Area Coverage Of The Wall-climbing Robot For Bridge Detection

Wall-climbing robot is an important branch of mobile robot,which provides a novel method for of bridge disease detection.While the wall-climbing robot execute a coverage task in bridge tower,bridge piers and other vertical surface,due to the influence of gravity,the energy consumption along each direction is different.Besides,problems such as GPS signal outage and limited battery life make the coverage technology of wall-climbing robot different from common mobile robot.From the above,research of an efficient coverage planning algorithm and appropriate positioning method to guide the wall-climbing robot is of great value.Firstly,energy consumption of the wall-climbing robot along the vertical direction is analyzed.Then,the energy consumption model of wall-climbing robot is established and the grid division method is applied to the vertical wall environment modelling.Secondly,the principle of the biologically-inspired neural network model is described,and the point-to-point path planning method based on biologically-inspired neural network is introduced.Next,we analyze the problem of original biologically inspired neural network method for coverage path planning.Based on the advantages of biologically inspired neural network and the energy consumption model of wall-climbing robot,the coverage path planning algorithm is proposed in this paper.Thirdly,the point-to-point path planning based on biologically-inspired neural network and the complete coverage planning algorithm of wall-climbing robot are verified by simulation contrast experiments.Considering the number and shape of the obstacles in the environment is uncertain,the barriers in the simulation contains U-shaped,L-shaped and oval obstacles and the number and position of the obstacles are generated randomly.By comparing with the existing coverage algorithms,the algorithm this paper proposed can ensure absolute coverage.Our method saves 24%and 15%energy compared with those complete coverage methods only concerning the activity of neurons and the algorithm in other paper respectively.Finally,due to the positioning demand of wall-climbing robot,the principle of ranging and calibration method based on UWB technology are introduced in detail.A wall positioning method based on UWB technology and IMU is proposed.Based on the positioning method and complete coverage algorithm above,we build an autonomous wall-climbing robot platform to realize autonomous traversal and carry out experiments of following a straight line and complete coverage in the environment with obstacle.The experimental results verify that wall-climbing robot can complete the specific area coverage task efficiently based on the proposed complete coverage algorithm,positioning method and the built platform.