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Mobile robot path planning method based on whale optimization algorithm

A mobile robot and optimization algorithm technology, applied in two-dimensional position/channel control, etc., to achieve the effect of easy movement, strong global search ability, and avoiding local optimum

Active Publication Date: 2019-05-17
CHONGQING UNIV OF POSTS & TELECOMM
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Problems solved by technology

Wang Jianhao and others proposed a whale optimization algorithm based on chaotic search strategy to improve the problem that the algorithm is easy to fall into local optimum in the later stage

Method used

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  • Mobile robot path planning method based on whale optimization algorithm
  • Mobile robot path planning method based on whale optimization algorithm
  • Mobile robot path planning method based on whale optimization algorithm

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Embodiment Construction

[0040] The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings in the embodiments of the present invention.

[0041] see figure 1 , the invention provides a mobile robot path planning method based on the whale optimization algorithm, comprising the following steps:

[0042] S1, initialize the whale optimization algorithm, set the parameters of the algorithm, set the number of whale populations to N, and set the maximum number of iterations to t max .

[0043] The selected fitness function is:

[0044]

[0045] Among them, X i is the position of the i-th whale, n represents the dimension of the individual whale in the search space, (x n ,y n ) represents the coordinates of the whale individual in the nth dimension on the grid map. Similarly, (x n+1 ,,y n+1 ) represents the coordinates of the whale individual in dimension n+1 on the grid map. represents the dimensionality of the whale population....

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Abstract

The invention discloses a mobile robot path planning method based on a whale optimization algorithm. The method comprises the following steps: step S1, initializing the whale optimization algorithm, setting parameters of the algorithm, using a fitness function to obtain fitness values of a whale at all positions, and determining an initial individual optimal position and a global optimal positionof a whale population; step S2, using a new convergence factor, re-calculating a coefficient vector and updating the new position of the whale individual; step S3, calculating the fitness value of thewhale individual at the new position and comparing the fitness value with the fitness value of the original position; step S4, if the fitness value of the new position is superior than the fitness value of the original position, updating the individual best position of the whale population, and updating the global optimal position; and step S5, after reaching the number of iterations, selecting awhale path with the minimum fitness value as the optimal path for the mobile robot path planning, otherwise, executing steps S2 to S4. The mobile robot path planning method based on the whale optimization algorithm provided by the invention has high convergence precision, fast convergence speed, and can avoid falling into local optimum in the later stage of the algorithm iteration.

Description

technical field [0001] The invention belongs to the technical field of robot path planning, in particular to a mobile robot path planning method based on a whale optimization algorithm. Background technique [0002] Mobile robot path planning is an important part of the robot's autonomous navigation system. It mainly solves the problem of "where to go" and "how to go" based on the prior map of the environment obtained by the robot. Its purpose is to find a collision-free safe path from the start point to the end point in a given environment map with obstacles, according to the evaluation criteria of the shortest distance, minimum time or minimum cost. In 2016, Australian scholar Mirjalili and others abstracted the mathematical model of the three behaviors of whales searching, encircling and attacking during predation based on the behavior of whales preying on prey, and proposed a new optimization algorithm based on swarm intelligence, namely the whale optimization algorithm ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/02
Inventor 罗元方继康张毅
Owner CHONGQING UNIV OF POSTS & TELECOMM
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