Comments (7)
Hello I would like to ask you another question, we are in the process of buying an Avia sensor to experiment with your FAST_LIO package, I managed to install your github on a virtual machine with ubuntu 18.04 LTS and also on jetson TX2 Nvidia which is a system recommended by DJI for livox systems, the github is all compiled. Do you think the system also works on tx2? I would like to avoid buying 2c manifold too which costs a lot and is not available here in Italy. What do you advise me to do, have you done any tests on a computer with jetson TX2? My team and I would like to put your system on a dji drone to carry out tests on hollow mining sites in very large spaces even 400mt to verify the accuracy of the clouds, then we will compare your system with a TOPCON laser scanner to analyze the differences. We would be interested in integrating precise GNSS positioning to your system to georeference and orient the cloud topographically, within 2cm of precision. Are you developing something to merge IMU and PointClaud data with Rinex data? There are very cheap UBLOX modules such as ublox FP9 that can manage dual band L1 L2 gnss signals which, if doubled, can create the baseline for orientation in space topographically. It would be interesting to combine your Fast_Lio package with a LOG system with satellite rinex data that aligns the cloud with centimeter precision which could then in post processing reach below the centimeter and color the clouds with a Sony a6000 camera. Hello from Italy.
Thanks for your interests in our works.
Here are something you may be interested in.
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We will launch Fast-LIO 2.0 in coming March. The Fast-LIO 2.0 will support the real-time implementation in embedded systems including TX2, Raspberry Pi 4 and other ARM-based platforms. But current version of Fast-LIO cannot guarantee the real-time performance in TX2, especially for the Large-scale space. If you are still interested in implementing Fast-lio, please wait for the Fast-LIO 2.0.
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FAST-LIO is focused on the fusion of IMU and LiDAR, not considering other sensor like GPS or Vision. But our MaRS Lab will propose some research projects that fusion other sensors, in a few months. So stay tuned!
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You can try to repeat "CMake" several times.
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sorry but the fast_lio / states library where is it? it shouldn't be in the include directory of your package, otherwise how can it compile? Where should it be?
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sorry but the fast_lio / states library where is it? it shouldn't be in the include directory of your package, otherwise how can it compile? Where should it be?
thanks for your suggestion,the states.h is automatically generated by the state.msg file in /msg folder. This is a common ros technique
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Hello I would like to ask you another question, we are in the process of buying an Avia sensor to experiment with your FAST_LIO package, I managed to install your github on a virtual machine with ubuntu 18.04 LTS and also on jetson TX2 Nvidia which is a system recommended by DJI for livox systems, the github is all compiled. Do you think the system also works on tx2? I would like to avoid buying 2c manifold too which costs a lot and is not available here in Italy. What do you advise me to do, have you done any tests on a computer with jetson TX2? My team and I would like to put your system on a dji drone to carry out tests on hollow mining sites in very large spaces even 400mt to verify the accuracy of the clouds, then we will compare your system with a TOPCON laser scanner to analyze the differences. We would be interested in integrating precise GNSS positioning to your system to georeference and orient the cloud topographically, within 2cm of precision. Are you developing something to merge IMU and PointClaud data with Rinex data? There are very cheap UBLOX modules such as ublox FP9 that can manage dual band L1 L2 gnss signals which, if doubled, can create the baseline for orientation in space topographically. It would be interesting to combine your Fast_Lio package with a LOG system with satellite rinex data that aligns the cloud with centimeter precision which could then in post processing reach below the centimeter and color the clouds with a Sony a6000 camera. Hello from Italy.
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@XW-HKU is FAST_LIO 2.0 the same as r2live?
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@XW-HKU is FAST_LIO 2.0 the same as r2live?
r2live use fast-lio2 as lidar-inertial front-end.
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Related Issues (20)
- Possibility of Using LIO on Point Cloud Created From Depth Cameras HOT 1
- Segmentation fault in ikd-tree rebuild process, cause by "Add_by_points". HOT 2
- 建图到一半,直接停止增量建图,前面的部分也开始逐个消失 HOT 1
- About Robosense M1 Lidar HOT 1
- fatal error: fast_lio/Pose6D.h: No such file or directory. HOT 1
- fastlio+livox HOT 1
- velodyne not fit into this project. HOT 2
- About NCLT Dataset ground truth HOT 1
- Downsampling Error HOT 1
- Livox MID-360 FAST_LIO2 建图过程中地图消失问题
- Gmapping navigation HOT 3
- The fineness of point cloud display in rviz HOT 1
- 里程计输出频率问题? HOT 1
- FAST_LIO uses only one core of the CPU HOT 1
- Is IMU optional? HOT 3
- 话题/Laser_map为空 HOT 3
- Some Clarification in Code HOT 2
- Is livox_ros_driver2 required at all? HOT 3
- process has died exit code 11 HOT 4
- How to get a trajectory format that can be used for evo tool ? HOT 1
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