Improvement on mobile robot path planning method based on ant colony algorithm

Abstract

The invention relates to a mobile robot path planning method. The method comprises the following steps: finding the shortest path of an environment; taking grids safe from a dynamic barrier on the shortest path as local target points when a robot detects in progress the dynamic barrier and will bump into the dynamic barrier in the environment; determining the motion range of the dynamic barrier; the robot advancing along the grids with high pheromone concentration; and obtaining an optimal path that is away from the dynamic barrier and passes by a specified point. The problem of low convergence speed of an ant colony algorithm due to restrictions of the ant colony algorithm itself is solved. A group of optimal solutions is obtained after parameters of a conventional ant colony algorithm are optimized by a particle swarm algorithm. A genetic algorithm is adopted to prevent local optimum, other parameters of the above parameters keep unchanged, and the pheromone concentration is amplified by times. In this way, pheromone concentration differences on different paths are more obvious, and the convergence speed of the algorithm is increased.

Description

technical field [0001] The invention relates to the technical field of path planning for mobile robots, relates to the speed of convergence of path planning for mobile robots, and in particular to a path planning method and algorithm for mobile robots. Background technique [0002] With the continuous development of human society and the continuous expansion of living space, mobile robots are more and more widely used in national defense, earthquake relief, disaster prevention and relief, anti-terrorism, modern military weapons, manufacturing and daily life. Dynamic routing for more efficient planning. With the rapid development of mobile robot technology and the continuous expansion of the application range, people put forward higher requirements for the performance of robots in all aspects. Through unremitting efforts, scientists have proposed a variety of path planning algorithms for mobile robots, and the ant colony algorithm is one of them. It is extracted based on th...

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Problems solved by technology

[0004] The purpose of the present invention is to provide a mobile robot path planning method to solve the problem of slow convergence of the ant colony algorithm due to its own limitations. After optimizing the parameters in the traditional ant colony algorithm with particle swarm algorithm, a group The optimal solution, and use the genetic algorithm to ensure that it will not fall into the local optimum, then keep the other parameters in the above parameters unchanged, and multiply the pheromone concentration to make the difference of pheromone concentration on different paths more obvious. Thereby improving the convergence speed of the algorithm

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