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A new genetic algorithm approach to smooth path planning for mobile robots

Baoye Song (College of Electrical Engineering and Automation, Shandong University of Science and Technology , Qingdao, China)
Zidong Wang (College of Electrical Engineering and Automation, Shandong University of Science and Technology , Qingdao, China and Department of Computer Science, Brunel University London , Uxbridge, Middlesex, UK)
Li Sheng (College of Information and Control Engineering, China University of Petroleum (East China) , Qingdao, China)

Assembly Automation

ISSN: 0144-5154

Article publication date: 4 April 2016

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Abstract

Purpose

The purpose of this paper is to consider the smooth path planning problem for a mobile robot based on the genetic algorithm (GA) and the Bezier curve.

Design/methodology/approach

The workspace of a mobile robot is described by a new grid-based representation that facilitates the operations of the adopted GA. The chromosome of the GA is composed of a sequence of binary numbered grids (i.e. control points of the Bezier curve). Ordinary genetic operators including crossover and mutation are used to search the optimum chromosome where the optimization criterion is the length of a piecewise collision-free Bezier curve path determined by the control points.

Findings

This paper has proposed a new smooth path planning for a mobile robot by resorting to the GA and the Bezier curve. A new grid-based representation of the workspace has been presented, which makes it convenient to perform operations in the GA. The GA has been used to search the optimum control points that determine the Bezier curve-based smooth path. The effectiveness of the proposed approach has been verified by a numerical experiment, and some performances of the obtained method have also been analyzed.

Research limitations/implications

There still remain many interesting topics, for example, how to solve the specific smooth path planning problem by using the GA and how to promote the computational efficiency in the more grids case. These issues deserve further research.

Originality/value

The purpose of this paper is to improve the existing results by making the following three distinctive contributions: a rigorous mathematical formulation of the path planning optimization problem is formulated; a general grid-based representation (2n × 2n) is proposed to describe the workspace of the mobile robots to facilitate the implementation of the GA where n is chosen according to the trade-off between the accuracy and the computational burden; and the control points of the Bezier curve are directly linked to the optimization criteria so that the generated paths are guaranteed to be optimal without any need for smoothing afterwards.

Keywords

Acknowledgements

This work was supported in part by the Research Fund for the Taishan Scholar Project of Shandong Province of China and the Higher Educational Science and Technology Program of Shandong Province of China under Grant J14LN34.

Citation

Song, B., Wang, Z. and Sheng, L. (2016), "A new genetic algorithm approach to smooth path planning for mobile robots", Assembly Automation, Vol. 36 No. 2, pp. 138-145. https://doi.org/10.1108/AA-11-2015-094

Publisher

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Emerald Group Publishing Limited

Copyright © 2016, Emerald Group Publishing Limited