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Hi, thanks for opensourcing this great work. I have two questions about the experiments.
First, in your paper, you use "END-TO-END POSITION ERROR IN METERS" to characterize the performance of different LIOs on FR-IOSB and KA-URBAN datasets. I want to run other LIOs on your datasets, so is it possible to provide the ground truth start and end positions you use in calculating the end-to-end position errors? Or at least a ground truth relative translation between the start and end positions of each trajectory (assuming identity 6dof pose at start)?
Another question is about the end-to-end location selection. Your paper mentions that KA-Urban Data Set is collected "with end-to-end locations registered from satellite images", I wonder,
since LiLi-OM already has a centimeter-level precision, how do you register even more precise positions on the satellite images (Google map I presume) as ground truth?
what about end-to-end locations in FR-IOSB Data Set?
Thank you.
The text was updated successfully, but these errors were encountered:
Hi, thanks for opensourcing this great work. I have two questions about the experiments.
First, in your paper, you use "END-TO-END POSITION ERROR IN METERS" to characterize the performance of different LIOs on FR-IOSB and KA-URBAN datasets. I want to run other LIOs on your datasets, so is it possible to provide the ground truth start and end positions you use in calculating the end-to-end position errors? Or at least a ground truth relative translation between the start and end positions of each trajectory (assuming identity 6dof pose at start)?
Another question is about the end-to-end location selection. Your paper mentions that KA-Urban Data Set is collected "with end-to-end locations registered from satellite images", I wonder,
Thank you.
The text was updated successfully, but these errors were encountered: