Mapping System Autonomous Electric Vehicle Based on Lidar-Sensor Using Hector SLAM Algorithm - SUPRAPTO Bhakti Yudho; DWIJAYANTI Suci; WIJAYA Patrick Kesuma (Journal of Electrical and Electronics Engineering, 2024)
Autonomous electric vehicles (EVs) need to recognize the surrounding environment through mapping. The mapping provides directions for driving in new locations and uncharted areas. However, few studies have discussed the mapping of unknown outdoor areas using light detection and ranging (LiDAR) with simultaneous localization and mapping (SLAM). LiDAR can reduce the limitations of GPS, which cannot track the current location, and it covers a limited area. Hence, this study used the Hector SLAM algorithm, which maps based on the data generated by LiDAR sensors. This study was conducted at the Universitas Sriwijaya using two routes: the Palembang and Inderalaya campuses. A comparison is made with the map on Google Maps to determine the accuracy of the algorithm. The route of the Palembang campus was divided into four points: A-B-C-D; route AB exhibits the highest accuracy of 85.7%. In contrast, the route of the Inderalaya campus was established by adding routes with buildings closer to the road. A marker point was allocated on the route: A-B-C-D-E; route CE exhibits the highest accuracy of 83.6%. Overall, this study shows that the Hector SLAM algorithm and LiDAR can be used to map the unknown environment of autonomous EVs.