Results 1 to 10 of about 2,548 (110)

A Review of Multi-Sensor Fusion SLAM Systems Based on 3D LIDAR

Remote Sensing, 2022
The ability of intelligent unmanned platforms to achieve autonomous navigation and positioning in a large-scale environment has become increasingly demanding, in which LIDAR-based Simultaneous Localization and Mapping (SLAM) is the mainstream of research
Xiaobin Xu, Zhiying Tan
exaly   +3 more sources

GNSS/IMU/ODO/LiDAR-SLAM Integrated Navigation System Using IMU/ODO Pre-Integration [PDF]

Sensors, 2020
In this paper, we proposed a multi-sensor integrated navigation system composed of GNSS (global navigation satellite system), IMU (inertial measurement unit), odometer (ODO), and LiDAR (light detection and ranging)-SLAM (simultaneous localization and ...
Le Chang, Xiaoji Niu, Tianyi Liu
doaj   +2 more sources

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 ...
Qingqing Li, Tomi Westerlund, Zhuo Zou
exaly   +3 more sources

Short-range Lidar SLAM utilizing localization data of monocular localization [PDF]

ROBOMECH Journal, 2021
Simultaneous localization and mapping (SLAM) is a widely used technology in autonomous mobile robots, where sensors such as Lidar or cameras are typically used.
Sousuke Nakamura, Shunsuke Muto, Daichi Takahashi   +2 more
doaj   +2 more sources

A Review of 2D Lidar SLAM Research

Remote Sensing
Two-dimensional (2D) simultaneous localization and mapping (SLAM) is a key technology for intelligent indoor robots. By using a map generated via SLAM, the robot can navigate and perform specific tasks.
Xiaobin Xu, Zhiying Tan, Ran Yingying
exaly   +3 more sources

2D LiDAR SLAM Back-End Optimization with Control Network Constraint for Mobile Mapping [PDF]

Sensors, 2018
Simultaneous localization and mapping (SLAM) has been investigated in the field of robotics for two decades, as it is considered to be an effective method for solving the positioning and mapping problem in a single framework.
Jingren Wen, Chuang Qian, Jian Tang, Hui Liu, Wenfang Ye, Xiaoyun Fan   +5 more
doaj   +2 more sources

The Influence of Micro-Hexapod Walking-Induced Pose Changes on LiDAR-SLAM Mapping Performance [PDF]

Sensors
Micro-hexapods, well-suited for navigating tight or uneven spaces and suitable for mass production, hold promise for exploration by robot groups, particularly in disaster scenarios.
Hiroshi Seki, Yuhi Yamamoto, Sumito Nagasawa   +2 more
doaj   +2 more sources

A LiDAR-Intensity SLAM and Loop Closure Detection Method Using an Intensity Cylindrical-Projection Shape Context Descriptor

International Journal of Applied Earth Observation and Geoinformation, 2023
LiDAR Simultaneous Localization and Mapping (SLAM) is able to map unknown scene while online estimating the LiDAR’s pose. Traditional LiDAR SLAM frameworks mainly rely on geometric features in the environments, but ignore LiDAR intensity information ...
Bijun Li, Chuang Qian, Yongxing Cao
exaly   +3 more sources

VINA-SLAM: A Voxel-Based Inertial and Normal-Aligned LiDAR–IMU SLAM [PDF]

Sensors
Environments with sparse or repetitive geometric structures, such as long corridors and narrow stairwells, remain challenging for LiDAR–inertial simultaneous localization and mapping (LiDAR–IMU SLAM) due to insufficient geometric observability and ...
Ruyang Zhang, Bingyu Sun
doaj   +2 more sources

A Review of Dynamic Object Filtering in SLAM Based on 3D LiDAR

Sensors
SLAM (Simultaneous Localization and Mapping) based on 3D LiDAR (Laser Detection and Ranging) is an expanding field of research with numerous applications in the areas of autonomous driving, mobile robotics, and UAVs (Unmanned Aerial Vehicles).
Ziyu Zhao
exaly   +3 more sources