*May*

Cut-off strategy means to use only first N observations to do polyak averaging, and stop updating landmark after N observation.The cut-off strategy has two advantages:More robust than traditional polyak averaging in both global observation model and intermittent observation model Able to...

*May*

This week I've been revisiting the online EM for Hidden Markov Model [1]. The formulation between HMM and latent model is similar but there's a little different. I've also developed an performance evaluator to quantify and optimize the performance of our framework, especially the choice of learnin...

*Apr*

Over the past week, I've successfully transforming the range-bearing measurements to direct observation with correct statistics (without approximation) Now the algorithm is fully functional.Here is the demo setting:maximum range radius: 25 cm range uncertainty: 0.5 cm^2 bearing uncertainty...

*Apr*

Improved algorithm with direct observation: Debugging on why range-bearing measurements failed: Attempted algorithm with range-bearing (perfect rnb observation, noisy time update): Attempted algorithm with range-bearing (noisy rnb observation, perfect time update): Still, problem aris...

*Apr*

For previous two weeks I was building up the framework of EM-SLAM. The framework is showed as following:And as well as the demo by using direct observation (states can be directly observed with gaussian noise):This demo works properly as expected (although there are some discrepency betwee...

*Mar*

Attached is a simple demo on one-step update of EM-SLAM algorithm. Note that the robot has only one observation at the begining, and then with an EM algorithm, the landmarks will converge to a certain configuration, but not exact position due to the prior guess of robot state has error. With a corre...

*Mar*

This week I was trying to derive the mathematical formulation of one-step update for recursive EM-SLAM algorith. I was referring to both batch EM-SLAM paper as well as recursive EM paper for reference, and I figured out a coarse representation of Q-function. While I am still doubt on how to get rid...

*Feb*

This week I was mainly surveying on puplications for recursive EM methods (not restricted to SLAM) in various applications, which is listed below: (1) Online EM algorithm for latent model This paper is more like a tutorial on how to use recursive EM algorithm to estimate parameter and update latent...

*Jan*

To debug what causes the divergence of EM-SLAM algorithm, I Separated E-step and M-step. To prove M-step is correct, every time I will feed a true Q-function from E-step to M-step. i.e. x=x_true, P=0. (Note in general, Q-function contains trajectory information and it is always estimated in E-step)....