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Improved ant colony algorithm based mobile robot path planning method

A mobile robot, ant colony algorithm technology, applied in the direction of instrument, calculation, calculation model, etc., can solve the problems of slow convergence speed, poor stability of optimization results, etc., to achieve the effect of improving efficiency and stability

Active Publication Date: 2019-08-06
ANHUI UNIVERSITY OF TECHNOLOGY AND SCIENCE
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AI Technical Summary

Problems solved by technology

However, with the deepening of research, the shortcomings of using ant colony algorithm for robot path planning are gradually discovered, such as local optimum, slow convergence speed, poor stability of optimization results, etc.

Method used

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  • Improved ant colony algorithm based mobile robot path planning method
  • Improved ant colony algorithm based mobile robot path planning method
  • Improved ant colony algorithm based mobile robot path planning method

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Embodiment Construction

[0048] Such as figure 1 As shown, the present invention provides a mobile robot path planning method based on the improved ant colony algorithm, comprising the following steps:

[0049] S1. Use the grid method to create a map of the robot's working environment, and define the starting point and target point;

[0050] S2. Using the ant colony algorithm to find the shortest path in the environment, the ant colony algorithm includes the following steps:

[0051] S21. Initialize the parameters of the ant colony algorithm;

[0052] S22. Put m ants on the starting point, add the starting point into the taboo table, start searching, and obtain the feasible path node grid;

[0053] S23. Each ant selects the next step to move the grid according to the formula (1), and adds the current grid to the taboo table;

[0054]

[0055] In formula (1), s is the current location node with transition probability, Select the transition probability of position node j for ant k at position no...

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Abstract

The invention discloses an improved ant colony algorithm based mobile robot path planning method. The method comprises the following steps that S1) a grid method is used to create an environment map of a robot; S2) an ant colony algorithm is used to search for a shortest environment path, and the ant colony algorithm comprises the following steps of S21) initializing parameters of the ant colony algorithm, S22) placing m ants in the initial points and starting searching, S23) selecting a next moving grid by using a distance heuristic function, S24) determining whether all ants arrive at a target point, moving to S25) if YES, and otherwise, returning to S23), S25) optimizing all feasible paths of present iteration in a route redundancy elimination strategy; S26) updating pheromones in a path deviation amplification strategy; and S27) determining whether the maximal iteration frequency is reached, ending if YES, and otherwise, adding 1 to the iteration times and returning to the step S22); and S3) the shortest path obtained in the step S2) is used as a planned optimal path. The global optimal solution is improved, and the convergence speed is improved.

Description

technical field [0001] The invention relates to the technical field of robot path planning, in particular to a path planning method for a mobile robot based on an improved ant colony algorithm. Background technique [0002] Path planning technology is an important part of the research field of mobile robots. The main purpose is to find a path from the starting position node in the environment with obstacles according to certain criteria (such as the shortest path, the least position inflection point, the shortest time, etc.). The optimal or suboptimal safe collision-free path between nodes to the target location. [0003] The development of path planning technology marks the level of robot intelligence to a certain extent, and the pros and cons of path planning methods directly affect the path planning effect. [0004] At present, many experts and scholars at home and abroad are working on the research of path planning algorithms. The commonly used optimization algorithms m...

Claims

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Application Information

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IPC IPC(8): G01C21/20G06N3/00
CPCG01C21/20G06N3/006
Inventor 王雷李东东李雪
Owner ANHUI UNIVERSITY OF TECHNOLOGY AND SCIENCE
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