Mobile robot path planning method and system based on genetic ant colony algorithm
A mobile robot, path planning technology, applied in navigation computing tools and other directions, can solve the blindness of ant colony algorithm and other problems
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Embodiment 1
[0070] Such as figure 1 and figure 2 As shown, the present embodiment 1 provides a mobile robot path planning method, including the following steps:
[0071] Step S1, modeling the environment by establishing a coordinate system;
[0072] Step S2, converting a part of the optimized solution obtained by the genetic algorithm into the initial value of the pheromone of the ant colony algorithm;
[0073] In step S3, the path optimization is carried out through the ant colony algorithm, and after the optimization is completed, the crossover operation is performed on the qualified paths, and finally the optimal path is obtained.
[0074] As an optional implementation of environment modeling, the method for modeling the environment by establishing a coordinate system in step 1 includes: using the environment detection device that comes with the mobile robot to model the environment to generate a random initial path.
[0075] Specifically, the environment modeling is to take the s...
Embodiment 2
[0113] Such as figure 1 and figure 2 As shown, on the basis of embodiment 1, this embodiment 2 provides a mobile robot path planning system, including:
[0114] The environment modeling module is used to model the environment by establishing a coordinate system;
[0115] A pheromone obtaining module for obtaining an initial value of the pheromone of the ant colony algorithm, and
[0116] An optimal path acquisition module connected with the pheromone acquisition module.
[0117] Wherein, the environment modeling module generates a random initial path by using the environment detection device of the mobile robot to model the environment; the environment detection device includes: a camera, a sonar ring, and an infrared sensor of the mobile robot.
[0118] And, the pheromone obtaining module is suitable for converting a part of the optimized solution obtained by the genetic algorithm into the initial value of the pheromone of the ant colony algorithm; that is, initializing t...
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