[IEEE ICRA'23] A new lightweight LiDAR-inertial odometry algorithm with a novel coarse-to-fine approach in constructing continuous-time trajectories for precise motion correction.
Hi, i recently read the papers of your group and i got some questions.
The first is in the paper "Direct LiDAR-Inertial Odometry and Mapping: Perceptive and Connective SLAM". I wonder that how did you add that connectivity factor into your factor graph? did you just calculated a relative pose using the result from front-end odometer when two these two non-adjacent keyframes having sufficient overlap and used your 3D Jaccard index calculated a noise?
The second is in the paper "Joint On-Manifold Gravity and Accelerometer Intrinsics Estimation for Inertially Aligned Mapping". Did the gravity factor you calculated was only used in the mapping stage and not added into the factor graph you mentioned before? And i also curious that you projected the gravity and covariance calculated in factor graph in inertial frame to body frame, and projected the fixed gravity in inertial frame to body frame, then used these two gravity as error function, why don't you just calculated the error in the inertial frame?
Thank you for your contribution of open-sourceing your code to the community. Looking forward to your reply.
kennyjchen
commented
1 month ago
Hi, i recently read the papers of your group and i got some questions. The first is in the paper "Direct LiDAR-Inertial Odometry and Mapping: Perceptive and Connective SLAM". I wonder that how did you add that connectivity factor into your factor graph? did you just calculated a relative pose using the result from front-end odometer when two these two non-adjacent keyframes having sufficient overlap and used your 3D Jaccard index calculated a noise? The second is in the paper "Joint On-Manifold Gravity and Accelerometer Intrinsics Estimation for Inertially Aligned Mapping". Did the gravity factor you calculated was only used in the mapping stage and not added into the factor graph you mentioned before? And i also curious that you projected the gravity and covariance calculated in factor graph in inertial frame to body frame, and projected the fixed gravity in inertial frame to body frame, then used these two gravity as error function, why don't you just calculated the error in the inertial frame? Thank you for your contribution of open-sourceing your code to the community. Looking forward to your reply.