Cooperative Multi-Robot Navigation–SLAM, Visual Odometry and Semantic Segmentation

Robert G. Reid, Kai Li Lim, Thomas Bräunl

Research output: Chapter in Book/Conference paperChapterpeer-review


The University of Western Australia's multi-robot system (MRS) comprises seven Pioneer 3AT-based outdoor robots. This chapter presents a decentralized multi-robot system for simultaneous localization and mapping (SLAM) in urban outdoor environments together with visual odometry and semantic segmentation techniques. Local SLAM is performed independently on each unmanned ground vehicle (UGV) whereby a single-robot SLAM algorithm builds its own submap by processing its sensor data, which is then broadcasted across the mesh network. The incorporation of semantic segmentation into the MRS enables navigation to be supplemented with scene understanding and object classification. Like visual odometry, semantic segmentation was also implemented in a decentralized approach onto individual UGVs. Static objects are stationary, while dynamic objects are moving. It is important for an multi-robot SLAM system to differentiate static and dynamic objects to devise proper navigational reactions to the environment. For an MRS to properly navigate an environment and perform cooperative tasks, these localization estimates need to be robust.
Original languageEnglish
Title of host publicationCooperative Localization and Navigation
Subtitle of host publicationTheory, Research, and Practice
EditorsChao Gao, Guorong Zhao, Hassen Fourati
Place of PublicationUSA
PublisherCRC Press
Number of pages18
ISBN (Electronic)9780429507229
Publication statusPublished - 21 Aug 2019


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