Fusing GNSS and wheel measurements based on FAST-LIO and IKFOM - FAST-LIO-Multi-Sensor-Fusion/package.xml at master · mfkiwl/FAST-LIO-Multi-Sensor-Fusion
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126 -- 0:17 App CMax SLAM testing using tub_main_building 4369 -- 1:28 App Loc-NeRF:Monte Carlo Localization using Neural Radiance Fields 3530 -- 10:23 App Multi-sensor fusion for VLP-SLAM localization and navigation 1万 -- 7:28 App Gaussian Splatting SLAM 4226 -- 3:01 App Orbe...
To achieve accurate and robust pose estimation in Simultaneous Localization and Mapping (SLAM) task, multi-sensor fusion is proven to be an effective solution and thus provides great potential in robotic applications. This paper proposes FAST-LIVO, a fast LiDAR-Inertial-Visual Odometry system, which...
Sensor fusion is the most used approach to overcome the first two shortcomings of the LiDAR in the LiDAR-based system. It has been proven that integrating LiDAR and other sensors with complementary properties, such as the inertial sensors and cameras, can improve the state estimation accuracy [8...
To improve positioning accuracy and reduce power consumption, multi-source fusion positioning system triggers specific positioning and fusion strategies according to the results of IO detection. Smartphones automatically adjust screen brightness according to the IO status and environment condition (e.g., ...
fastlio_testing3 SplaTAM Testing using TUM-Dataset freiburg1_room_seed0(训练过程可视化) Point-line LIVO Using Patch-Based Gradient Optimization for Degenerate Scenes envio_testing3 fastlio_testing4 大疆livox-mid360定位 LONER:LiDAR Only Neural Representations for Real-Time SLAM ...
Rosbag Filesa python scriptpython3 sensordata_to_rosbag_fastlio.py bin_file_dir bag_name.bag Run: roslaunch fast_lio_msf mapping_velodyne.launch rosbag play YOUR_DOWNLOADED.bag 5.Implementation on UAV In order to validate the robustness and computational efficiency of FAST-LIO in actual mobil...
FAST-LIO-Multi-Sensor-Fusion Fusing GNSS and wheel measurements based on FAST-LIO and IKFOM Fusing GNSS measurement and support GNSS heading auto-initialization. Fusing wheel measurement and support the estimation of wheel extrinsic parameters and wheel scale factor meanwhile. Tested on the Kaist Comp...
Depending on the type of sensor used, mainstream SLAM systems are typically categorized into single-sensor SLAM, such as LiDAR-based [27,28,29,30] and vision-based [12,13,14,15,16], and multi-sensor fusion SLAM techniques [31,32,33,34,35], integrating various sensors to enhance SLAM ...