LIO-SAM and ORB SLAM for localization. The requirement of the project to localize the robot with an accuracy of 10cm in the world coordinates were tested out with both the mentioned SLAM based APIs. The picture given to the left is the visualization of LIO SAM in a feature rich environment. LIO SAM produced high precision in localization with an error of only 2 cm to the ground truth.

RTK-GPS for high precision localization. The system was able to overcome the limitation of ORB-SLAM and LIO-SAM which would fail when the environment is feature deficient. The RTK GPS localized the robot with an error of 8 cm even when it is at a plain and isolated area.

Worked on drivers that can be used in ROS workspace. Component testing done for accuracy measurement.