Results 31 to 40 of about 15,287 (197)
STRATEGIES TO INTEGRATE IMU AND LIDAR SLAM FOR INDOOR MAPPING [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 In recent years, the importance of indoor mapping increased in a wide range of applications, such as facility management and mapping hazardous sites. The essential technique behind indoor mapping is simultaneous localization and mapping (SLAM) because ...
S. Karam, V. Lehtola, G. Vosselman
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FLAT2D: Fast localization from approximate transformation into 2D [PDF]
, 2016 Many autonomous vehicles require precise localization into a prior map in order to support planning and to leverage semantic information within those maps (e.g.
Goeddel, Robert +3 more
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Research on SLAM Algorithm of Mobile Robot Based on the Fusion of 2D LiDAR and Depth Camera
IEEE Access, 2020 This paper proposes a new Simultaneous Localization and Mapping (SLAM) method on the basis of graph-based optimization through the combination of the Light Detection and Ranging (LiDAR), RGB-D camera, encoder and Inertial Measurement Unit (IMU).
Lili Mu +5 more
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LIDAR-INERTIAL NAVIGATION BASED ON MAP AIDED DISTANCE CONSTRAINT AND FACTOR GRAPH OPTIMIZATION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023 The simultaneous localization and mapping (SLAM) is one of the well-developed positioning technology that provides high accuracy and reliability positioning for automatic vehicles and robotics applications. Integrating Light Detection and Ranging (LiDAR)
M. Ai +3 more
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Consistent ICP for the registration of sparse and inhomogeneous point clouds [PDF]
, 2016 In this paper, we derive a novel iterative closest point (ICP) technique that performs point cloud alignment in a robust and consistent way. Traditional ICP techniques minimize the point-to-point distances, which are successful when point clouds contain ...
Goeman, Werner +3 more
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Deep Learning-Aided Inertial/Visual/LiDAR Integration for GNSS-Challenging Environments
Sensors, 2023 This research develops an integrated navigation system, which fuses the measurements of the inertial measurement unit (IMU), LiDAR, and monocular camera using an extended Kalman filter (EKF) to provide accurate positioning during prolonged GNSS signal ...
Nader Abdelaziz, Ahmed El-Rabbany
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Scan matching by cross-correlation and differential evolution [PDF]
, 2019 Scan matching is an important task, solved in the context of many high-level problems including pose estimation, indoor localization, simultaneous localization and mapping and others.
Konečný, Jaromír +3 more
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Weighted Conformal LiDAR-Mapping for Structured SLAM
IEEE Transactions on Instrumentation and Measurement, 2023 One of the main challenges in simultaneous localization and mapping (SLAM) is real-time processing. High-computational loads linked to data acquisition and processing complicate this task. This article presents an efficient feature extraction approach for mapping structured environments. The proposed methodology, weighted conformal LiDAR-mapping (WCLM),
Natalia Prieto-Fernández +5 more
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Towards online mobile mapping using inhomogeneous lidar data [PDF]
, 2016 In this paper we present a novel approach to quickly obtain detailed 3D reconstructions of large scale environments. The method is based on the consecutive registration of 3D point clouds generated by modern lidar scanners such as the Velodyne HDL-32e or
Goeman, Werner +4 more
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A Review of Simultaneous Localization and Mapping Algorithms Based on Lidar
World Electric Vehicle JournalSimultaneous localization and mapping (SLAM) is one of the key technologies for mobile robots to achieve autonomous driving, and the lidar SLAM algorithm is the mainstream research scheme.
Yong Li +6 more
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