Mobile robot path planning method based on self-adaptive ant colony algorithm

Abstract

In order to overcome the defects that in the prior art, when a traditional ant colony algorithm is used for solving a path, algorithm stagnation and falling into a local optimal solution are likely tohappen, the invention discloses a mobile robot path planning method based on the self-adaptive ant colony algorithm, and the method comprises the following steps: step 1, modeling by a grid environment method; step 2, performing initial pheromone differential distribution; step 3, improving transition probability; step 4, improving pheromone updating rule: when the algorithm drop frequency reaches a set threshold value, readjusting a pheromone volatilization coefficient and a pheromone concentration; and step 5, a segmented third-order Bezier curve carrying out smoothing processing on an optimal path. According to the invention, the algorithm convergence rate and the optimization capability can be coordinated at the same time, the rationality of mobile robot path planning is improved, andthe robot moving speed is increased.

Description

technical field [0001] The present invention relates to the technical field of robot path planning, in particular to a mobile robot path planning method based on an adaptive ant colony algorithm. Background technique [0002] The problem of path planning for mobile robots is a hotspot in the field of robot research, and it is also the basis of robot control. It requires robots to operate in a given working environment according to certain standards (such as the shortest time, the shortest distance, the lowest energy consumption, etc.). Search for an optimal or near-optimal safe path. At present, many traditional algorithms are used in the path planning of mobile robots. With the deepening of research, some bionic intelligent optimization algorithms are gradually applied to path planning research. Compared with traditional algorithms, bionic intelligent optimization algorithms have more advantages in solving path planning problems in complex environments. [0003] Ant Colo...

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Problems solved by technology

[0005] In order to solve the shortcomings of the traditional ant colony algorithm in the prior art, which is prone to algorithm stagnation and local optimal solution when solving the path, the present invention discloses a mobile robot path planning method based on the adaptive ant colony algorithm, which can solve the problem of The traditional ant colony algorithm often falls into the problem of local optimum, and at the same time, it can coordinate the convergence speed and optimization ability of the algorithm at the same time

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