Title: Research on intelligent path planning technology of logistics robots based on Giraph architecture

Authors: Xin Xiong; Runan Huang; Cuixian He

Addresses: School of Intelligent Manufacturing, Guangzhou Panyu Polytechnic, Vanke Golden Chengpin C4-801, No. 818 Dexian Road, Shawan Town, Panyu District, Guangzhou City, Guangdong Province, 511483, China ' School of Intelligent Manufacturing, Guangzhou Panyu Polytechnic, Shawan Market, Panyu District, Guangzhou, Guangdong, 511483, China ' School of Intelligent Manufacturing, Guangzhou Panyu Polytechnic, Shawan Market, Panyu District, Guangzhou, Guangdong, 511483, China

Abstract: In the development of modern e-commerce, the logistics robot is an important part of the intelligent warehouse. Especially in large-scale warehouses, the operation efficiency of logistics robots largely depends on the processing ability of patrol efficiency. In order to solve the problems of difficult path planning and complex operation in the logistics robot operating system, based on the analysis of the traditional path algorithm, an improved logistics robot path planning algorithm based on graph architecture, CAA*path planning algorithm, is proposed and used to solve the conflict-free path planning problem of the logistics robot in the intelligent logistics warehouse. The improved CAA*path planning algorithm is compared with the traditional a*algorithm, ant colony algorithm, simulated annealing algorithm, ant colony optimisation algorithm and genetic algorithm. The simulation analysis shows that the improved CAA*path planning algorithm is more efficient in time operation. Under the same number of tasks and the same map specification, the improved CAA*path planning algorithm takes less time and runs more efficiently.

Keywords: logistics robot; Giraph architecture; route planning; cloud computing; intelligence; warehouse.

DOI: 10.1504/IJCSM.2022.128190

International Journal of Computing Science and Mathematics, 2022 Vol.16 No.3, pp.252 - 264

Received: 24 Nov 2021
Received in revised form: 25 May 2022
Accepted: 19 Jul 2022
Published online: 11 Jan 2023 *

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