Robot welding path planning based on improved ant colony algorithm

For the basic ant colony algorithm in the robot welding path planning, some problems such as too long searching time, low efficiency and falling into local optimum in the process of searching were found. For the basic ant colony algorithm, Adadelta algorithm was introduced in this paper. By updating the parameters of Adadelta algorithm, the update of ant pheromones was improved and the volatility coefficient of pheromones was improved. The adaptive method was adopted to update pheromones. The improved algorithm was simulated with MATLAB and the result analysis show that the improved ant colony algorithm in this paper had better search capability than the basic ant colony algorithm and higher algorithm efficiency, which was about 20 generations ahead of the basic ant colony algorithm. The method in this paper effectively solved the local optimization and slow convergence speed of the basic ant colony algorithm and made the search results better.