Robosense M1 in FAST-LIO2 and LIO-SAM

[FrancoVigier]

@RuanJY
Hi, I'm Franco from Argentina. I'm working also with LIDAR M1 and FAST-LIO2. I have a couple of questions about the adaptations you made to FAST-LIO2:

1. Is there a repository with the adaptations?
2. What handler did you use to process the PointCloud2 points? In my case I used Preprocess::default_handler(), and it showed a lot of drift in the odometry displayed by rviz2.
3. What type of points did you use XYZI or XYZIRT?
4. How did you treat the NaN points of the M1? Did you enable dense_cloud: True (in robosense sdk config) to filter them or not?
5. Did you use an external ros2 package to convert the robosense points to velodyne?
6. In the yaml parameters of FAST_LIO when you had to set the accelerometer and gyro covariances, those values correspond to the covariance and random walk of each sensor?

[RuanJY]

Thanks for your interest on our work. 1. Is there a repository with the adaptations? yes, we will also open our adaptions later. 2. What handler did you use to process the PointCloud2 points? In my case I used Preprocess::default_handler(), and it showed a lot of drift in the odometry displayed by rviz2. we write a new handler. I think the drift may due to the timestamp issue, notice that timestamp of robosense LiDAR is different from livox LiDAR. 3. What type of points did you use XYZI or XYZIRT? include timestamp 4. How did you treat the NaN points of the M1? Did you enable dense_cloud: True (in robosense sdk config) to filter them or not? remove NaN points in code 5. Did you use an external ros2 package to convert the robosense points to velodyne? now we use ros1. 6. In the yaml parameters of FAST_LIO when you had to set the accelerometer and gyro covariances, those values correspond to the covariance and random walk of each sensor? my advise is that you should carefully check the timestamp of each points, which is also our main modification on FASTLIO2 —

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---- Replied Message ---- From Franco Vallejos ***@***.***><mailto:undefined> Date 12/6/2024 02:57 To ***@***.***>***@***.***> Cc ***@***.***>, ***@***.***>***@***.***>***@***.***> Subject [RuanJY/HK_MEMS_Dataset] Robosense M1 in FAST-LIO2 and LIO-SAM (Issue #2) CAUTION: This email is not originated from PolyU. Do not click links or open attachments unless you recognize the sender and know the content is safe. @RuanJY<https://github.com/RuanJY> Hi, I'm Franco from Argentina. I'm working also with LIDAR M1 and FAST-LIO2. I have a couple of questions about the adaptations you made to FAST-LIO2: 1. Is there a repository with the adaptations? 2. What handler did you use to process the PointCloud2 points? In my case I used Preprocess::default_handler(), and it showed a lot of drift in the odometry displayed by rviz2. 3. What type of points did you use XYZI or XYZIRT? 4. How did you treat the NaN points of the M1? Did you enable dense_cloud: True (in robosense sdk config) to filter them or not? 5. Did you use an external ros2 package to convert the robosense points to velodyne? 6. In the yaml parameters of FAST_LIO when you had to set the accelerometer and gyro covariances, those values correspond to the covariance and random walk of each sensor? — Reply to this email directly, view it on GitHub<#2>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/AF3YWJH52B4NJYR76E4EBO32ECO2XAVCNFSM6AAAAABTDDX5EGVHI2DSMVQWIX3LMV43ASLTON2WKOZSG4ZDCMJXG43DCNI>. You are receiving this because you were mentioned.Message ID: ***@***.***> [https://www.polyu.edu.hk/emaildisclaimer/PolyU_Email_Signature-v2.jpg] Disclaimer: This message (including any attachments) contains confidential information intended for a specific individual and purpose. If you are not the intended recipient, you should delete this message and notify the sender and The Hong Kong Polytechnic University (the University) immediately. Any disclosure, copying, or distribution of this message, or the taking of any action based on it, is strictly prohibited and may be unlawful. The University specifically denies any responsibility for the accuracy or quality of information obtained through University E-mail Facilities. Any views and opinions expressed are only those of the author(s) and do not necessarily represent those of the University and the University accepts no liability whatsoever for any losses or damages incurred or caused to any party as a result of the use of such information.