S4-SLAM: A real-time 3D LIDAR SLAM system for ground/watersurface multi-scene outdoor applications
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S4-SLAM: A real-time 3D LIDAR SLAM system for ground/watersurface multi-scene outdoor applications Bo Zhou1 · Yi He1 · Kun Qian1 · Xudong Ma1 · Xiaomao Li2 Received: 23 March 2019 / Accepted: 11 September 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract For outdoor ground/watersurface multi-scene applications with sparse feature points, high moving speed and high dynamic noises, a real-time 3D LIDAR SLAM system (S4-SLAM) for unmanned vehicles/ships is proposed in this paper, which is composed of the odometry function in front-end and the loop closure function in back-end. Firstly, linear interpolation is used to eliminate the motion distortion caused by robot motions in the data pre-processing step. Two nodes are constructed in the odometry function: the localization node combines the improved Super4PCS with the standard ICP to realize a coarse-to-fine scan matching and outputs the location information of the robot at a high frequency (5 Hz); the correction node introduces a local map with dynamic voxel grid storage structure, which can accelerate the NDT(Normal Distributions Transform) matching process between key-frames and the local map, and then corrects the localization node at a low frequency (1 Hz) to obtain more accurate location information. In the loop closure function, a location-based loop detection approach is introduced and the overlap rate of point clouds is used to verify the loops, so that the global optimization can be carried out to obtain high-precision trajectory and map estimates. The proposed method has been extensively evaluated on the KITTI odometry benchmark and also tested in real-life campus and harbor environments. The results show that our method has low dependence on GPS/INS, high positioning accuracy (with the global drift under 1%) and good environmental robustness. Keywords Multi-scene mapping · LIDAR odometry · SLAM · Loop detection · Scan matching
1 Introduction With the development of unmanned driving, real-time localization and navigation research for outdoor mobile robots or unmanned vehicles are receiving more and more attentions. The common solution for navigation tasks of unmanned vehicles at present is heavily relied on high-precision maps and GPS/INS information. However, when GPS data and highprecision maps are not available, SLAM (Simultaneously Localization and Mapping) is thought to be a good substitute to solve the above problems. Visual SLAM and LIDAR
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Xiaomao Li [email protected] Bo Zhou [email protected]
1
School of Automation, Southeast University, Nanjing 210096, People’s Republic of China
2
School of Mechatronic Engineering and Automation, Shanghai University, Shanghai 200000, People’s Republic of China
SLAM are two commonly used outdoor SLAM approaches. While visual SLAM algorithms are greatly influenced by the intensity of light, the optical structure and the texture features of environments, the robustness of the system is often challenged, especially for long-term large-scale scenes applications. In contrast, t
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