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Open AccessArticle

A Novel RGB-D SLAM Algorithm Based on Cloud Robotics

by Yanli Liu *,†, Heng Zhang *,† and Chao Huang
School of Information Engineering, East China Jiaotong University, Nanchang 330013, China
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Sensors 2019, 19(23), 5288; https://doi.org/10.3390/s19235288
Received: 11 October 2019 / Revised: 27 November 2019 / Accepted: 28 November 2019 / Published: 1 December 2019
In this paper, we present a novel red-green-blue-depth simultaneous localization and mapping (RGB-D SLAM) algorithm based on cloud robotics, which combines RGB-D SLAM with the cloud robot and offloads the back-end process of the RGB-D SLAM algorithm to the cloud. This paper analyzes the front and back parts of the original RGB-D SLAM algorithm and improves the algorithm from three aspects: feature extraction, point cloud registration, and pose optimization. Experiments show the superiority of the improved algorithm. In addition, taking advantage of the cloud robotics, the RGB-D SLAM algorithm is combined with the cloud robot and the back-end part of the computationally intensive algorithm is offloaded to the cloud. Experimental validation is provided, which compares the cloud robotic-based RGB-D SLAM algorithm with the local RGB-D SLAM algorithm. The results of the experiments demonstrate the superiority of our framework. The combination of cloud robotics and RGB-D SLAM can not only improve the efficiency of SLAM but also reduce the robot’s price and size. View Full-Text
Keywords: RGB-D SLAM; cloud robotics; ROS; 3D point cloud RGB-D SLAM; cloud robotics; ROS; 3D point cloud
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Liu, Y.; Zhang, H.; Huang, C. A Novel RGB-D SLAM Algorithm Based on Cloud Robotics. Sensors 2019, 19, 5288.

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