Improved ant colony algorithm integrating Kalman filtering prediction thought and suitable for mobile robot navigation
A Kalman filter, mobile robot technology, applied in two-dimensional position/channel control, instruments, motor vehicles and other directions, can solve the problems of increasing the initial pheromone heuristic effect, insufficient pheromone heuristic effect, etc., to improve the heuristic effect, The effect of promoting fast convergence and improving algorithm performance
Active Publication Date: 2022-03-25
HENAN UNIVERSITY OF TECHNOLOGY
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[0006]
The purpose of the present invention is to solve the technical problem that the existing ant colony algorithm is applied to the path planning of mobile robots. Pheromone global initialization distribution calculation, increasing the heuristic effect of initial pheromone
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[0026] The technical solutions of the present invention will be described in further detail below through specific implementation methods.
[0027] 1, the present invention provides a kind of improved ant colony algorithm that is applicable to mobile robot navigation of fusion Kalman filter prediction idea, comprises the following steps:
[0028] Step 1: Construct a two-dimensional grid map according to the usage scenario of the mobile robot. At the same time, set the map parameters such as the starting point of the robot movement, the destination point, and the initial obstacle information.
[0029] Step 2: According to Step 1, set parameters such as ant colony size, number of iterations, pheromone evaporation rate, heuristic information weight factor and pheromone weight factor in the ant colony algorithm. At the same time, set the initial ant colony algorithm pheromone distribution according to the initial distribution rules of pheromones, and start the ant colony algorith...
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The invention provides an improved ant colony algorithm which is fused with a Kalman filtering prediction thought and is suitable for mobile robot navigation. The improved ant colony algorithm comprises the following steps: introducing a pheromone initial distribution rule to initialize pheromone global distribution, and improving an initial pheromone inspiration effect; the composite node selection strategy fused with the optimal node prediction model is adopted to perform node selection in the ant path-finding process, and the optimal node selection probability is increased; the prediction pheromone updating model fused with the Kalman filtering thought is used for carrying out optimal updating on the global pheromone concentration, and the optimal fusion and prediction are carried out according to two times of pheromone numerical values before and after iteration, so that the pheromone enlightening effect is improved; the pheromone weight factor and the heuristic information weight factor in the ant colony algorithm node probability formula are dynamically updated in a dynamic updating mode, and algorithm convergence is accelerated. The method has a high heuristic effect on the ant colony algorithm process, the defects that the ant colony algorithm is low in convergence speed, low in precision and the like in the mobile robot path planning process are overcome, and the algorithm efficiency is improved.
Description
technical field [0001] The present invention relates to the field of mobile robot navigation technology. Specifically, the mobile robot navigation technology is mainly path planning technology, and relates to an improved ant colony algorithm that is suitable for mobile robot navigation and integrates Kalman filter prediction ideas, and is used to speed up mobile robot navigation. The speed and accuracy of path planning improves the performance of mobile robot navigation algorithms. Background technique [0002] Navigation is an essential technology in the development of mobile robots. Mobile robot navigation technology is mainly path planning technology. At present, there are many kinds of algorithms used for mobile robot path planning, mainly iterative algorithm and biological heuristic algorithm. Among them, biological heuristic algorithm is also an iterative algorithm to some extent. For path planning algorithms, it mainly includes A* algorithm, genetic algorithm, artifi...
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IPC IPC(8): G05D1/02
CPCG05D1/0217G05D1/0221Y02D30/70
Inventor 刘建娟刘忠璞薛礼啟吴豪然李志伟陈红梅姬淼鑫张会娟袁航
Owner HENAN UNIVERSITY OF TECHNOLOGY