Abstract
In this work, we present a comparative analysis of the trajectories estimated from various Simultaneous Localization and Mapping (SLAM) systems in a simulation environment for vineyards. Vineyard environment is challenging for SLAM methods, due to visual appearance changes over time, uneven terrain, and repeated visual patterns. For this reason, we created a simulation environment specifically for vineyards to help studying SLAM systems in such a challenging environment. We evaluated the following SLAM systems: LIO-SAM, StaticMapping, ORB-SLAM2, and RTAB-MAP in four different scenarios. The mobile robot used in this study equipped with 2D and 3D lidars, IMU, and RGB-D camera (Kinect v2). The results show good and encouraging performance of RTAB-MAP in such an environment.
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Notes
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wiki.ros.org/rtabmap_ros.
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Field: youtu.be/L9ORZNyWdT0. Uneven terrain: youtu.be/L9ORZNyWdT0.
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This work has been supported by the European Commission as part of H2020 under grant number 871704 (BACCHUS).
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Hroob, I., Polvara, R., Molina, S., Cielniak, G., Hanheide, M. (2021). Benchmark of Visual and 3D Lidar SLAM Systems in Simulation Environment for Vineyards. In: Fox, C., Gao, J., Ghalamzan Esfahani, A., Saaj, M., Hanheide, M., Parsons, S. (eds) Towards Autonomous Robotic Systems. TAROS 2021. Lecture Notes in Computer Science(), vol 13054. Springer, Cham. https://doi.org/10.1007/978-3-030-89177-0_17
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