Optimal autonomous mobile robot motion planning for green logistics

V. Sathiya and M. Chinnadurai

International Journal of Productivity and Quality Management, 2019, vol. 28, issue 1, 68-89

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.

Keywords: green logistics; green warehouse; autonomous mobile robot; multi objective optimal motion planning; elitist non-dominated sorting genetic algorithm; NSGA-II; multi objective differential evolution; fuzzy logic. (search for similar items in EconPapers)
Date: 2019
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