Results 11 to 20 of about 14,971 (201)
AGPC-SLAM: Absolute Ground Plane Constrained 3D Lidar SLAM
Navigation, 2022 3D lidar-based simultaneous localization and mapping (SLAM) is a well-recognized solution for mapping and localization applications. However, the typical 3D lidar sensor (e.g., Velodyne HDL-32E) only provides a very limited field of view vertically. As a
Weisong Wen, Li-Ta Hsu
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VILO SLAM: Tightly Coupled Binocular Vision–Inertia SLAM Combined with LiDAR
Sensors, 2023 For the existing visual–inertial SLAM algorithm, when the robot is moving at a constant speed or purely rotating and encounters scenes with insufficient visual features, problems of low accuracy and poor robustness arise.
Gang Peng +6 more
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SLAM-based 3D outdoor reconstructions from lidar data [PDF]
2018 International Conference on 3D Immersion (IC3D), 2018 The use of depth (RGBD) cameras to reconstruct large outdoor environments is not feasible due to lighting conditions and low depth range. LIDAR sensors can be used instead. Most state of the art SLAM methods are devoted to indoor environments and depth
Caminal Colell, Ivan +2 more
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ART-SLAM: Accurate Real-Time 6DoF LiDAR SLAM [PDF]
IEEE Robotics and Automation Letters, 2022 Real-time six degree-of-freedom pose estimation with ground vehicles represents a relevant and well studied topic in robotics, due to its many applications, such as autonomous driving and 3D mapping. Although some systems exist already, they are either not accurate or they struggle in real-time setting.
Matteo Frosi, Matteo Matteucci
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SC-LiDAR-SLAM: A Front-end Agnostic Versatile LiDAR SLAM System
2022 International Conference on Electronics, Information, and Communication (ICEIC), 2022 Accurate 3D point cloud map generation is a core task for various robot missions or even for data-driven urban analysis. To do so, light detection and ranging (LiDAR) sensor-based simultaneous localization and mapping (SLAM) technology have been elaborated.
Kim, Giseop +3 more
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INDOOR MAPPING: EXPERIENCES WITH LIDAR SLAM
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 Abstract. Indoor mapping is gaining more interest in both research as well as in emerging applications. Building information systems (BIM) and indoor navigation are probably the driving force behind this trend. For accurate mapping, the platform trajectory reconstruction, or in other words sensor orientation, is essential to reduce or even eliminate ...
B. Suleymanoglu +3 more
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Semantic Lidar-Inertial SLAM for Dynamic Scenes
Applied Sciences, 2022 Over the past few years, many impressive lidar-inertial SLAM systems have been developed and perform well under static scenes. However, most tasks are under dynamic environments in real life, and the determination of a method to improve accuracy and ...
Zean Bu, Changku Sun, Peng Wang
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Remote Sensing, 2022 Reliable absolute positioning is indispensable in long-term positioning systems. Although simultaneous localization and mapping based on light detection and ranging (LiDAR-SLAM) is effective in global navigation satellite system (GNSS)-denied ...
Zhijian Chen +6 more
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A Benchmark for Multi-Modal LiDAR SLAM with Ground Truth in GNSS-Denied Environments
Remote Sensing, 2023 LiDAR-based simultaneous localization and mapping (SLAM) approaches have obtained considerable success in autonomous robotic systems. This is in part owing to the high accuracy of robust SLAM algorithms and the emergence of new and lower-cost LiDAR ...
Ha Sier +5 more
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Exploration-Based SLAM (e-SLAM) for the Indoor Mobile Robot Using Lidar [PDF]
Sensors, 2022 This paper attempts to uncover one possible method for the IMR (indoor mobile robot) to perform indoor exploration associated with SLAM (simultaneous localization and mapping) using LiDAR. Specifically, the IMR is required to construct a map when it has landed on an unexplored floor of a building.
Hasan Ismail +4 more
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