Autonomous Vehicles Projects
Ecole Centrale de Nantes | Sep 2020 - Feb 2021 | Nantes, FRA
A collection of autonomous vehicles projects I have developed in my time in ECN. You can experiment yourself with the project and find the source code, report and more multimedia in the following link.
Iterative closest point
Iterative Closest Point Algorithm can be done in Python with the Nuscenes data set as in Algorithm 1 shown in the report. The general idea is that given two corresponding point clouds from the LiDAR measurement (in this case, called source and target), the motion (rotation and translation) done by the vehicle can be determined in a closed form.
Occupancy grid mapping
The occupancy grid map shown below is the result of the MS.c. Thesis I carried on in collaboration with WYCA Robotics. It shows the evolution of the occupancy grid map of the office generated by the remap routine developed using an SLAM algorithm in ROS2. The source code and further details are confidential; however, the animation below showcases that the results obtained were successful.
