Optimal Robot Path Planning for Multiple Goals Visiting Based on Tailored Genetic Algorithm

23Citations
Citations of this article
26Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Abstract: In real applications, mobile robot may be commanded to go to multiple goals to execute special commissions. This study analyzes the particular properties of this multiple goals visiting task and proposes a novel tailored genetic algorithm for optimal path planning for this task. In proposed algorithm, objectives for evaluating the path are energy consumption and idle time that are proposed in our previous work. Under the constraint of energy consumption, it will generate an optimal path that comprises as more goals as possible and as less idle time as possible. In this algorithm, customized chromosome representing a path and genetic operators including Repair, Cut and Deletion are developed and implemented. Afterwards, simulations are carried out to verify the effectiveness and applicability. Finally, analysis of simulation results is conducted and future work is addressed.

Cite

CITATION STYLE

APA

Liu, F., Liang, S., & Xian, X. (2014). Optimal Robot Path Planning for Multiple Goals Visiting Based on Tailored Genetic Algorithm. International Journal of Computational Intelligence Systems, 7(6), 1109–1122. https://doi.org/10.1080/18756891.2014.963978

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free