An Improved Ant Colony Algorithm for Solving the Path Planning Problem of the Omnidirectional Mobile Vehicle

Joint Authors

Zhao, Jiang
Cheng, Dingding
Hao, Chongqing

Source

Mathematical Problems in Engineering

Issue

Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-10, 10 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2016-09-19

Country of Publication

Egypt

No. of Pages

10

Main Subjects

Civil Engineering

Abstract EN

This paper presents an improved ant colony algorithm for the path planning of the omnidirectional mobile vehicle.

The purpose of the improved ant colony algorithm is to design an appropriate route to connect the starting point and ending point of the environment with obstacles.

Ant colony algorithm, which is used to solve the path planning problem, is improved according to the characteristics of the omnidirectional mobile vehicle.

And in the improved algorithm, the nonuniform distribution of the initial pheromone and the selection strategy with direction play a very positive role in the path search.

The coverage and updating strategy of pheromone is introduced to avoid repeated search reducing the effect of the number of ants on the performance of the algorithm.

In addition, the pheromone evaporation coefficient is segmented and adjusted, which can effectively balance the convergence speed and search ability.

Finally, this paper provides a theoretical basis for the improved ant colony algorithm by strict mathematical derivation, and some numerical simulations are also given to illustrate the effectiveness of the theoretical results.

American Psychological Association (APA)

Zhao, Jiang& Cheng, Dingding& Hao, Chongqing. 2016. An Improved Ant Colony Algorithm for Solving the Path Planning Problem of the Omnidirectional Mobile Vehicle. Mathematical Problems in Engineering،Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1112600

Modern Language Association (MLA)

Zhao, Jiang…[et al.]. An Improved Ant Colony Algorithm for Solving the Path Planning Problem of the Omnidirectional Mobile Vehicle. Mathematical Problems in Engineering No. 2016 (2016), pp.1-10.
https://search.emarefa.net/detail/BIM-1112600

American Medical Association (AMA)

Zhao, Jiang& Cheng, Dingding& Hao, Chongqing. An Improved Ant Colony Algorithm for Solving the Path Planning Problem of the Omnidirectional Mobile Vehicle. Mathematical Problems in Engineering. 2016. Vol. 2016, no. 2016, pp.1-10.
https://search.emarefa.net/detail/BIM-1112600

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1112600