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About the usage of the dataset. #5
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Thanks for your interest in our work. The lidar scan .npy file is a numpy array of scan range values. You can directly use python np.load() to read the npy file and obtain the scanning range values, and you can find the scanning bearing values (the angle range and resolution) based on the specific lidar sensor installed on the robot. The maximum range is also based on the specific lidar sensor, but I manually cut it off to 30 meters when I used it. |
@zzuxzt |
Note that x_r and y_c are the grid indices of the OGM (x_row, y_column) rather than the physical coordinates. The range of x_r and y_c is [0, 64] in our paper. |
@zzuxzt |
This is because we use the predicted coordinate frame as the reference frame and need to transfer the coordinates of all the past lidar sequences to the predicted coordinate frame. The predicted coordinate frame (future pose of the robot) is the same for all the past lidar sequences. |
Thank you for answering my questions. |
Hi, @zzuxzt!
Great work, thanks for sharinig it with the community! I am now working on Social-Nav and I am interested in occupancy grid prediction and planning. I noticed your dataset comes from the SCAND dataset but I am little confusing about how to use the npy files provided by you especially the "scan" part. Did you capture the ranges in the ROS bag files directly into your npy files? And I guess the max range is 30 meter?
Thank you
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