Abstract:
In this project, a line feature based EKF SLAM is implemented. There are two assumptions for the environment. First of all, the environment is two dimensional and thus it could be described by line features. Secondly, there is no moving object in the environment. There are two assumptions for estimators. First, both of the probability density functions (pdf) of input signal and noise are Gaussian distributions. Second, the Bayesian networks of SLAM obey Markov chain. Because the most indoor environments can be modeled as line features easily, there are many approaches of line feature based SLAM.
Instructor: Prof. Stergios Roumeliotis
Final Project: Line Features Based Simultaneous Localization and Mapping