Recently I started studying papers on SLAM systems by Durrant-Whyte for my research and I'm finding some difficulties in the math (matrices and probability) that is tackled in these papers.
Which math books/topics would you recommend me to go over before continuing with other papers?
Probability and statistics. Stochastic signal processing. Estimation and Detection theory (I highly recommend that you find a class that uses Harry VanTrees's book and that offers office hours, that you enroll, and study, and that you reserve lots of time in your schedule to take it -- if you can learn that stuff by reading the book you're somewhere in the 99.9th percentile).
"Optimal State Estimation" by Dan Simon is a really good Kalman filter book, but if you find yourself just reading the words and not getting the math, then you need to put it down and go study multivariate probability for a while.
Matrix math has been mentioned -- but you can know the matrix math up the wazoo, and all it does is make it quicker to formulate the problems. Without the knowledge of probability & statistics part, the matrix math will just help you screw up quicker, and with more elan.
The Probabilistic Robotics written by Thuran and his colleagues was completely helpful for me. Also, you can follow one of their colleague videos on youtube for SLAM.
