*Jul*

We simulation these SLAM algorithms with increasing duration. We can see that the estimation accuracy is comparable among 3 SLAM algorithms, but the processing times are different. The processing time is basically dominated by the optimization problem. The bigger the optimization problem, the long...

*Jun*

Following up with Alexie's post last week, we furthermore show that the simulation of BOEM SLAM algorithm for 1000 sec. The result is the average of 5 trials. The computation times for other algorithm, including optimization based and the EM SLAM, are too large for 1000 sec, but we have the comparis...

*Jun*

We compare 3 different SLAM algorithms on EuRoC datasets. As for estimation accuracy, we can see that all SLAM algorithms can improve the accuracy upon the visual-inertial odometry VIO output. The optimization SLAM has the most consistent result, while all SLAM algorithms have comparable perform...

*May*

The optimization based SLAM formulate the optimization problem with two kinds of constraints. First, the pre-integrated IMU error establishes the constraints between two spatial states, or two poses. The other one is the reprojection error that links a spatial state and a landmark. In the optimizati...

*Apr*

We are now able to demonstrate that the performances of EM-based SLAM algorithms are comparable to that of optimization-based. However, it is not easy to observe that same thing in the real-world dataset. simulation result The first challenge is whether to use IMU data or to only use the output...

*Apr*

In our previous paper, we investigate the consensus problem with von Mises distribution. We want to extend our analysis to more general distributions, in particular the von Mises-Fisher (vMF) distribution over hyperspheres. In fact, vMF distributions are used in some machine learning algorithms. I...

*Feb*

error.pdf result_2.pdf I implemented the EM based SLAM algorithms. However, in a visual inertial system, we can to take care of other realistic issues besides the theoretical algorithm itself. It will be insightful to compare the optimization based algorithm, since it has been developed for a wh...

*Jan*

Optimization-based SLAM From the pre-optimization (blue line) to the post-optimization (orange line), we can see that the optimization method enables the loop closure effect. The key improvement lies in the better computer vision techniques by discarding possibly erroneous keypoints. Also, the...

*Dec*

Previously, I finished the feature matching and id assignment in the SLAM frontend. Last week, I combine the result with the preintegrated IMU data to formulate an optimization problem. Initial values I initialize the landmark position by triangulate two frames. The selection of these two points...

*Dec*

okvis is a visual odometry. Therefore, the feature matching only occurs within short time window, and the feature matching that enables loop closure is not provided. The following is the overview as well as the result of the feature matching that I implemented. Keyframe selection This part relie...