Mobile robot relocation method and mobile robot based on genetic algorithm

Abstract

The present invention is applicable to the technical field of relocation, and provides a mobile robot positioning method based on a genetic algorithm and a mobile robot, including the following steps: S1, loading a global map, and using an idle area as an effective area; S2, initializing a population; S3, based on The likelihood value of the closest obstacle distance is used to calculate the fitness of the initial individual; S4, select the optimal individual among the initial individuals; S5, increase the number of iterations by one, and perform iterative operations, that is, sequentially select, cross, mutate, and update the optimal Particle operation; S6. Check whether the number of iterations reaches the set number of iterations. If the detection result is yes, then output the current optimal individual, decode the floating-point code of the optimal individual, and the obtained pose is the optimal position. pose, based on the optimal pose to obtain the pose of the mobile robot in the global map, if the detection result is negative, go to step S5. Through the superior global search ability of the genetic algorithm, the robustness and efficiency of the relocation system are improved.

Description

technical field [0001] The invention belongs to the technical field of robot positioning, and provides a method for relocating a mobile robot based on a genetic algorithm and the mobile robot. Background technique [0002] Positioning is one of the most basic problems in the field of mobile robot research, and it has become the basis for mobile robots to achieve autonomous capabilities such as navigation and motion planning. It is the mobile robot's use of sensors to determine its own position in the environment. In the fields of automated factories, intelligent warehousing and logistics, and home services, when a mobile robot restarts or is suddenly "kidnapped" to another location, the robot will not be able to locate its position. At this time, the current location of the robot needs to be relocated. Among the existing solutions for robot relocation, some are to arrange auxiliary equipment in the environment to achieve robot positioning, which increases costs and has many ...

AI Technical Summary

Problems solved by technology

Among the existing solutions for robot relocation, some are to arrange auxiliary equipment in the environment to achieve robot positioning, which increases costs and has many limitations; some use particle filter positioning methods to solve global positioning and robot "kidnapping". "The problem has a good performance, but this method also has the problem of slow convergence speed and easy degradation of the algorithm.

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