Research On Robot Drilling Path Planning Algorithm Based On Aircraft Component Model

With the development of modern aircraft manufacturing industry,a high standard for aircraft assembly technology is put forward.The robot assembly system is based on the way of digital assembly,and the production of an aircraft needs thousands,or even tens of thousands of parts,and there are a lot of holes in the work process.A more efficient and high quality automated processing scheme is needed to replace the manual drilling and riveting processing manufacturing process.To improve the accuracy of the robot hole,it is necessary to choose the best path in the process of making holes.The basic problem is to determine a motion optimal path from the initial point to the target point in space.The robot path planning technology has become a hot research topic in the field of aviation manufacturing at home and abroad,and it is an important application technology and research direction of aircraft flexible assembly technology.In this paper,through the software of CATIA,the three-dimension model of aircraft components is built,the hole position design information(hole position,process information,etc.)is extracted and processed to provide the data base for robot automatic hole making.By analyzing the basic principle of path planning and path planning algorithm,particle swarm optimization algorithm and ant colony algorithm are used to solve the problem of path planning to realize the optimization goal of robot path planning.The simulation result shows that the particle swarm algorithm and ant colony algorithm have some shortcomings in solving the problem of robot path planning,so adaptive ant colony algorithm is applied and is compared and studied in the simulation to complete the drilling tasks on aircraft components.For the problem of robot path planning given,the results show that the adaptive ant colony algorithm is more accurate and stable than the traditional ant colony algorithm.Whether from the path length or the number of iterations,adaptive ant colony algorithm has a more fast convergence speed,less time of use and more short path length in robot path planning.It is superior to traditional ant colony algorithm.That algorithm is easier to search the target,and improve the convergence speed of the algorithm and the ability to search the global optimalvalue.