Advanced 3D Urban Mapping with LiDAR Sensors for Autonomous Driving and Real-World Testing

This project aims to overcome current limitations in autonomous vehicle navigation, specifically for the ANTA prototype at the Salesian Polytechnic University, by creating high-definition (HD) 3D maps. The core problem is the lack of precise maps adapted to the complex urban morphology of Cuenca, which causes geopositioning errors exceeding 20 cm in dynamic environments. The methodology integrates a mobile LIDAR scanning platform with inertial measurement units (IMU) and GPS to capture massive geospatial data. This data will be processed using advanced algorithms to generate HD maps that identify obstacles and signage with high fidelity. The system will be validated in three stages: simulation, field tests in diverse urban conditions, and technical evaluations by international experts from HanKaisi Intelligent. The expected impact is twofold: improving the navigation precision and operational safety of the ANTA vehicle, and establishing a reference laboratory for autonomous mobility in the Latin American context. This progress contributes to the Mobility as a Service (MaaS) ecosystem, promoting more efficient and sustainable urban transport, while generating scientific publications and strengthening the university's interdisciplinary research capacity.<br/><br/><b>Goal</b>: <br/>Develop an integrated 3D mapping system using LIDAR sensors to generate high-precision maps that enable the safe and efficient operation of autonomous vehicles. The project will validate this performance through driving tests in real urban environments.<br/><br/><b>Research lines</b>: <br/>Maintenance engineering applied to transportation<br/>Transportation and mobility