This projects implements graph-based SLAM (Simultaneous Localization and Mapping), a robust method for tracking an object over time and building a map of the environment, This is achieved through the use of sensor and motion data and he exploitation elements of probability, motion models, and linear algebra.
Below is an example of a 2D robot world with landmarks (purple x's) and the robot (a red 'o') located and found using only sensor and motion data collected by that robot.
Execute sequentially
Notebook 1 : Robot Moving and Sensing;
Notebook 2 : Omega and Xi, Constraints;
Notebook 3 : Landmark Detection and Tracking.
$ git clone https://github.com/kenkai21/Landmark_Detection_Tracking.git
$ sudo pip3 install -r requirements.txtThis project is licensed under the terms of the
