Authors:
Kun Ma¹², Chuangyue Hu¹, Yuzhi Zhang²
Affiliations:
¹ Jiaxing Yangtze Delta Region Blockchain Technology, Jiaxing, China
² College of Software, Nankai University, Tianjin, China
Corresponding Author:
Kun Ma ([email protected])
Journal Details:
Published in Interdisciplinary Research Perspectives, Vol. 1, Issue 1, 2025.
Abstract
Cartographer technology, a sophisticated method in the Simultaneous Localization and Mapping (SLAM) field, employs advanced laser and visual data fusion for accurate robot mapping and localization. Traditionally, Cartographer implementations have depended heavily on the robot’s own computing resources, often leading to computational delays and inefficient resource use. This paper introduced a novel cloud-based Cartographer framework, inspired by cloud robotics architecture, which aims to improve the efficiency of Cartographer across various robotic applications, significantly reducing computational demands and enhancing robot energy efficiency. Furthermore, the framework includes a hash elimination technique to boost data efficiency and increase overall energy savings. Experimental validations show that this framework significantly enhances the processing speed of Cartographer on cloud computing platforms, reduces robots’ energy consumption, and optimizes data transmission.