Hi, thanks for your great work. I used my lidar and imu to record the data set and run it in DLO. The following figure is the map generated by the algorithm. I found that IMU drift is very serious. Is this related to coordinate system transformation? How can I set up and configure files to improve this situation?

Thanks for your work, I want to use nanoicp to location, it cann`t work right, but I use the pcl Gicp， it can work, so, there is anything i need to do?

Hi, How is the map generated? What algorithm is used? Can we upload a pcd map of the environment and then apply dlo just for localisation? I assumed dlo as a localisation algorithm, but it seems to take in the point cloud data from the bag file and generate a map on its own.

I run source code each scan's gicp process just cost 2-3 ms, when i run my own code use gicp library it cost 100-200ms. Both Input cloud's size almost same, which setting options may cause this phenomenon?

i have a trouble understanding how to localise on a given 3d pcd map, can anyone explain the steps

i have a pcd map which i can load into rviz, and i have lidar-points and imu data, then how to use this package for localization?

Hello author, I want to derive the jacobian in the code. I see we use global perturbation to update. When i try this, i meet this problem to look for your help. When using Woodbury matrix identity it seems to make the formula more complicated, so i'm stuck to look for your help. Thanks for your help in advance!

Best regards Xiaoliang jiao

I use a vlp16 lidar and a microstran imu(3DM-GX5-25) to run your program. But I failed. I think my transformation between imu and lidar is different from yours. So could you tell your true transformation between imu and lidar. the following pitcure is my configuration: Thank you very much!

Hi! I use a vlp16 lidar and a microstran imu(3DM-GX5-25) to record bags. And here is the part of the map I built with your algorithm. Because the coordinate systems of IMU and lidar are not consistent in the physical direction, this has affected the construction of the two-layer environment. Could you please tell me how to convert IMU and lidar coordinate system?

Hello authors, I have some trivial questions to look for your help. Thanks for your help.

• diff rot is neither this->rotq.inverse() * closest_pose_r nor closest_pose_r.inverse() * this->rotq?
• quaternion to axis angle, rotation norm is theta_rad *=2; ?
• this->keyframe_cloud is the last keyframe, we should set curr keyframe into gicp_s2s.setInputSource(), before we calculate covariance, namely this->keyframe_cloud update should before we calculate covariance ?
• returned final rotation should be check whether to flip sign, rather than in publishPose() ?

Hi,

Thank you for sharing this great work.

I've set of problem such as defining the coordinate system of the odometry . Which coordinate frame do you use for odometry NED or BODY. I thought you use NED coordinate frame so that I expected when I move Lidar + IMU to the North direction, x should be positive increased but it has not been stable behaviour. I also moved the system to the East direction it should be caused positive increase on y axis but same problem. I think you use BODY frame or something different coordinate frame for odometry.

I wonder also how do you send odometry information to the autopilot of drone. I prefered mavros and selected the related odometry ros topic and send them without change so I saw the odometry message in the autopilot but when odometry receive to the autopilot of drone it looks like x and y exchanged in autopilot even they are not exchanged odometry output of direct lidar odometry.

Summary of the Question is that which coordinate frame do you use for odometry ? How can I set up the odometry frame to NED? x and y are negative decreased when I move lidar+imu to the North and the East respectively. and Z looks like 180 reversed. Should I multiply x and y with minus or apply rotation matrix to fix negative decreasing x, y odometry ?

How can I ensure that autopilot and your odometry coordinate plane are in the same coordinate plane ?

Hi, thank you for your great work about DLO. I have a question. When the robot is moving fast, the lidar point cloud will generate distortion due to movement, which will cause negative impact on the construction of the map. So how did DLO deal with this problem?