The Research Of Mobile Robot Path Planning Algorithm Based On Ant Colony Algorithm

Since 60s of the last century, the mobile robotic technology has made great progress after about 40 years development. In sewage treatment plants, as the poor environment, some work is not suitable for long time working for people. Therefore, the demands of automation operations are put forward. The inspection robot of sewage treatment plants is presented based on this background.Mobile robot path planning is a typical optimization problem, it is characterized with complexity, binding character and nonlinear. The state of sewage treatment plants is also very complex, so an efficient path planning algorithm is needed for the mobile robot of sewage treatment plants to travel by itself.The basic environment of sewage treatment plant is unchanged, so the global path planning of mobile robot is mainly researched in this dissertation. First of all, the development situation of robot path planning is overviewed, and the characteristics and development trends of a variety of algorithms are summarized. The robot path planning based on ant colony algorithm is adopted after many algorithms are compared. The basic principles, characteristics, some evaluation indexes and convergence are researched and analyzed in detail, and genetic algorithm is introduced to improve the efficiency of ant colony algorithm, to avoid falling into local optimum, and the convergence issue is solved. The Max-Min Ant System is used in the designation, the strategy of two-way parallel search and encounter are designed to improve the speed of generation of initial population of ant colony, the strategy of withdrawal to prevent the ants fall into the trap, heuristic search probability formula is designed to improve the search speed of ants, a large number of experiments are made to analyze the various parameters of ant colony algorithm, then the best combination of parameters is selected to further improve the efficiency of algorithm.Although the basic environment of sewage treatment plant is unchanged, in actual conditions, some minor changes may take place such as some cars park in a certain location or in the running, so the real intelligent robot need to be able to make the right path planning when the environment are changed. Therefore, the local path planning based on ant colony algorithm is researched, we do the exploration research on the dynamic obstacle-avoidance ant colony forecast algorithm and strategy of obstacle-avoidance.Based on the study of ant colony algorithm, environment map is established through grid method, and the software for robot path planning based on ant colony algorithm is compiled. An optimal path can be planed quickly by the software when the environment map is known. Many simulation experiments for the improved ant colony algorithm and the traditional ant colony algorithm are made through the software. We can find that the integrated performance index has been improved by analyze the experimental data, and the algorithm can converge faster in forepart, the overall efficiency and convergence speed of improved colony algorithm are improved.