Design and Analysis of Live Working Robot
In order to solve the problems of high strength, high risk and low efficiency of high-altitude live working, according to the working environment and requirements of bolt tightening, the live working robot with walking manipulator, working manipulator and box structure is designed. Then, in order to control the working manipulator more accurately, t he force relationship of each contact part in the bolt tightening process is analyzed, and the radial basis function (RBF) neural network algorithm is designed to control the end tool of the working manipulator. Finally, the error and convergence speed of RBF neural network algorithm are measured by Matlab simulation experiment. The results show that the robot has small control deviation and fast response, which can meet the requirements of live working. In order to further test the stability and reliability of live working robot, field robot operation test is carried out. The test results show that the robot has not over tightened or under tightened the bolts, which meets the stability requirements of the control system.