In this report, we document our solution for the coursework. We are looking at the problem of integrated navigation of a robotic lawnmower, using GNSS and Dead Reckoning (DR) sensor data. Our approach has 4 pillars: 1) initialising the position using GNSS 2) Outlier Detection in the data 3) use Kalman filter for the GNSS only positioning 4) use DR data to create a DR only solution, then integrate it with the GNSS positions using Kalman filter.
CatalinOAlexandru/Integrated-Navigation-for-Robotics
This is part of a group project for a master module. We are looking at the problem of integrated navigation of a robotic lawnmower, using GNSS and Dead Reckoning (DR) sensor data.
MATLAB