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Hey Josh thanks for your reply . I am using maplab as a slam algo as it takes imu data as an input Do you think there is something wrong with the imu data at timestamp 400 and beyond ? Or is it maplab doesn't detect key points on the video properly ? I am thinking of using extended kalman filter from 400 sec to 600 sec and using the output of maplab at ...


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The any way would be SLAM itself. The point of SLAM is to reconstruct a trajectory given sensor inputs. That's just semantics though. I'm guessing you want to know how to handle failed sensor cases. If so, you have to detect those cases and reject the results. This can be done with multi-hypothesis SLAM or particle filters, but are significantly more ...


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This depends on how you acquire your data. You can either manually label ground truth or use sensors such as GPS. I have used GPS data with RTK corrections (sub cm accuracy) as ground truth in the past. You could also place markers such as AR/april tags at known locations in your surroundings and use their measurements in your dataset as ground truth.


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