Localization and mapping are two fundamental parts of the navigation system of an autonomous robot. Mapping is the procedure that allows the robot, using the available sensors, to generate a map of the environment. Localization, instead, is the procedure that allows the robot, using its sensors and a map of the environment, to determine its position and orientation with respect to a fixed reference frame.
These two tasks, that are always not easy, are particularly complex when an outdoor agricultural scenario is considered, due to the light conditions, the seasonal variability, and the overall complexity of the natural environment.

This thesis aims at setting up and comparing the performance of different localization and mapping algorithms, or of simultaneous localization and mapping algorithms on some realistic agricultural datasets.

This work is more suitable for students with an engineering background and with a previous experience in coding using C, C++ or Python. A group of two students, one with an engineering background and one with a non engineering background would be the best choice.

Reference teacher: Prof. Luca Bascetta – luca.bascetta@polimi.it