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Title: Simultaneous localisation and mapping of intelligent mobile robots

Authors: Sufang Wang; Tingyang Xie; Peng Chen

Addresses: Beijing Institute of Computer Technology and Application, Beijing 100000, China ' Department of Computer Science and Engineering, The Ohio State University, Columbus 43210, Ohio, USA ' School of Mechanical Engineering, North China University of Science and Technology, Tangshan 063210, Hebei, China

Abstract: Simultaneous Localisation and Mapping (SLAM) is the key technology of mobile robot navigation. In this field, visual SLAM (VSLAM) has become a research hotspot in recent years. This article discusses the Lidar and visual SLAM algorithms, including: introduction on commonly used solutions and improvements of the Lidar SLAM algorithm and exploring related difficulties, the characteristics of monocular, binocular and RGB-D cameras in VSLAM, the ORB-SLAM2 system based on the feature extraction method, the LSD-SLAM system based on the direct method, and comprehensively understanding and comparing the advantages and disadvantages between Lidar SLAM and visual SLAM, trying to fully utilise the two systems' advantages to implement better abilities of autonomous localisation, path planning and obstacle avoidance. Finally, the conclusion section discusses the development direction of multi-sensor fusion SLAM and the intelligent application of mobile robots in multiple fields.

Keywords: simultaneous localisation and mapping; Lidar; visual SLAM; mobile robot; navigation; sensors.

DOI: 10.1504/IJCCPS.2021.113103

International Journal of Cybernetics and Cyber-Physical Systems, 2021 Vol.1 No.1, pp.93 - 104

Received: 28 Aug 2020
Accepted: 10 Sep 2020

Published online: 31 Jan 2021 *

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