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Frontiers of Information Technology & Electronic Engineering >> 2022, Volume 23, Issue 2 doi: 10.1631/FITEE.2000358

Novel robust simultaneous localization and mapping for long-term autonomous robots

Affiliation(s): School of Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen 518055, China; Zhuhai Big Data Research Institute, Zhuhai 519000, China; less

Received: 2020-07-18 Accepted: 2022-02-28 Available online: 2022-02-28

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Abstract

A fundamental task for mobile robots is . Moreover, is an important property for SLAM. When vehicles or robots steer fast or steer in certain scenarios, such as low-texture environments, long corridors, tunnels, or other duplicated structural environments, most SLAM systems might fail. In this paper, we propose a novel robust visual inertial navigation (VILN) SLAM system, including stereo visual-inertial LiDaR odometry and visual-LiDaR loop closure. The proposed VILN SLAM system can perform well with low drift after experiments, even when the LiDaR or visual measurements are degraded occasionally in complex scenes. Extensive experimental results show that the has been greatly improved in various scenarios compared to state-of-the-art SLAM systems.

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