LiDAR and IMU based positioning system integration for scenarios where GNSS and RTK fail to ensure high precision

The objective of this thesis is to design and implement a real-time positioning system for an autonomous agricultural robot. The system will be built using ROS2 packages and it will be tested in a gazebo environment to simulate some real scenario. The software will be integrated in an agricultural autonomous robot produced by Black-Shire, the robot’s name is RC3075. The robot already has some sensors to localize such as Global Navigation Satellite System (GNSS) and Real-Time Kinematics (RTK). The big problem with only these sensors is that when GPS signal is low quality, the positioning of the robot becomes difficult and inaccurate. To solve this problem, the positioning system will be modified. Some sensors will be added and the position will be calculated based on the new sensors. In the end the new positioning system will be tested in a simulation environment and in the real world. As LiDAR a multiscan 136 from SICK as been used. It is a 3D LiDAR with an integrated IMU. It also has a complete integration with ROS 2 with a complete package to download that will return messages on ROS 2 topics. A SLAM algorithm has been used. Cartographer from google has been chosen and tuned. In the end, a complete software has been implemented and tested in a real vineyard on the robot and the results were satisfactory. The robot has been tracked by the algorithm with no errors or significant problems.