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Hello author, After running Mins, I would like to see the effect of multi-sensor tight coupling positioning. The dataset I used was urban30.bag, but after running it for a while, I saw the following image:
From the figure, it can be seen that there are three paths in total, where green is path_imu, blue is path_imu_gt_lat, and yellow is path_gps0. What do these three lines represent respectively? Which is the path of multi-sensor fusion calculation result? Will the input truth file urban30.txt display a truth trajectory in the figure?
At the same time, I also noticed that after the program runs, an outputs/tmp file is generated, where 0.time is the total running time of the program. So, is 0.txt the result of multi-sensor fusion calculation?
Hope to receive your reply, thank you
The text was updated successfully, but these errors were encountered:
Hello author, After running Mins, I would like to see the effect of multi-sensor tight coupling positioning. The dataset I used was urban30.bag, but after running it for a while, I saw the following image:
From the figure, it can be seen that there are three paths in total, where green is path_imu, blue is path_imu_gt_lat, and yellow is path_gps0. What do these three lines represent respectively? Which is the path of multi-sensor fusion calculation result? Will the input truth file urban30.txt display a truth trajectory in the figure?
At the same time, I also noticed that after the program runs, an outputs/tmp file is generated, where 0.time is the total running time of the program. So, is 0.txt the result of multi-sensor fusion calculation?
Hope to receive your reply, thank you
The text was updated successfully, but these errors were encountered: