SLAM Overview: From Single Sensor to Heterogeneous Fusion
Remote Sensing, 2022 After decades of development, LIDAR and visual SLAM technology has relatively matured and been widely used in the military and civil fields. SLAM technology enables the mobile robot to have the abilities of autonomous positioning and mapping, which ...
Weifeng Chen +6 more
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Research on Environment Perception System of Quadruped Robots Based on LiDAR and Vision
Drones, 2023 Due to the high stability and adaptability, quadruped robots are currently highly discussed in the robotics field. To overcome the complicated environment indoor or outdoor, the quadruped robots should be configured with an environment perception system,
Guangrong Chen, Liang Hong
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MR-MD:MULTI-ROBOT MAPPING WITH MANHATTAN DESCRIPTOR [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2023 Simultaneous Localization and Mapping (SLAM) technology, utilizing Light Detection and Ranging (LiDAR) sensors, is crucial for 3D environment perception and mapping.
H. Wu +20 more
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Mobile Robot Self-Localization with 2D Push-Broom LIDAR in a 2D Map [PDF]
, 2020 This paper proposes mobile robot self-localization based on an onboard 2D push-broom (or tilted-down) LIDAR using a reference 2D map previously obtained with a 2D horizontal LIDAR.
Clotet Bellmunt, Eduard +3 more
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A Review of Visual-LiDAR Fusion based Simultaneous Localization and Mapping
Sensors, 2020 Autonomous navigation requires both a precise and robust mapping and localization solution. In this context, Simultaneous Localization and Mapping (SLAM) is a very well-suited solution.
César Debeunne, Damien Vivet
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Consistent map building in petrochemical complexes for firefighter robots using SLAM based on GPS and LIDAR [PDF]
, 2018 The objective of this study was to achieve simultaneous localization and mapping (SLAM) of firefighter robots for petrochemical complexes. Consistency of the SLAM map is important because human operators compare the map with aerial images and identify ...
Amano, Hisanori +9 more
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LiDAR Point Cloud Generation for SLAM Algorithm Evaluation [PDF]
Sensors, 2021 With the emerging interest in the autonomous driving level at 4 and 5 comes a necessity to provide accurate and versatile frameworks to evaluate the algorithms used in autonomous vehicles. There is a clear gap in the field of autonomous driving simulators.
Łukasz Sobczak +3 more
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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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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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