Multi-robot Feature-based SLAM using Submap Joining

Chen，Shengduo1,2; Han，Ruihua1,3; Zhao，Liang2; Hang，Shoudong2; Hao，Qi1

2021

1448-2053

Australasian Conference on Robotics and Automation, ACRA

2021-December

This paper considers the feature-based SLAM using multiple robots. To reduce the computational complexity and data storage, a distributed multi-robot feature-based SLAM algorithm under submap joining scheme is proposed. Each robot first independently builds a submap using the information collected by its sensors. Once the robots can observe each other, the submaps can then be fused together to obtain a global map. We implemented and tested the proposed algorithm in both simulation and real world environments. Both simulation and experimental results have validated the robustness and accuracy of the proposed algorithm.

第一 ; 通讯

英语

2-s2.0-85124508928

Scopus

1.Department of Computer Science and Engineering,Southern University of Science and Technology,Shenzhen,518055,China
2.Robotics Institute of University of Technology,Sydney,Australia
3.The Department of Computer Science,The University of Hong Kong,Hong Kong

Chen，Shengduo,Han，Ruihua,Zhao，Liang,et al. Multi-robot Feature-based SLAM using Submap Joining[C],2021.