Optimal autonomous mobile robot motion planning for green logistics
by V. Sathiya; M. Chinnadurai
International Journal of Productivity and Quality Management (IJPQM), Vol. 28, No. 1, 2019

Abstract: In 2017, CO2 emissions from logistics activities is 0.82 million tons across the world. Introduction of low exhaust emission vehicles, reduction in transportation distance, introduction of electrical vehicles, improvement in load factor, reduction in cost, fast delivery are goals of green logistics. To accomplish these goals, Autonomous mobile robots are good choice. This paper proposes a good method for improving the performance of a warehouse robot by a multi objective optimal motion planning. Wheeled mobile robot is considered. Two multi objective optimisation algorithms [elitist non-dominated sorting genetic algorithm (NSGA-II) and multi objective differential evolution (MODE)] are used. A cubic NURBS curve constructs the robot path. Four multi objective performance metrics and two methods are utilised to examine the performance of MODE and NSGA-II algorithms. The results from a numerical simulation proved that the suggested method is a good idea to improve the green warehouse operations and to do necessary automation.

Online publication date: Tue, 24-Sep-2019

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Productivity and Quality Management (IJPQM):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com