Abstract
The usage of a LIDAR-based obstacle detection system in agricultural environment, as developed in SOLCO project, has led to a novel detection strategy. The rural scenario can be rather complex in terms of background, type and size of the obstacles encountered. In the experimentation, a strategy was applied to several trials in rural scenarios, with the aim of finding and fine tuning an object filtering approach that can be later applied in runtime. This strategy could be transferred to passenger car applications to improve LIDAR system performances.
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Acknowledgments
The field testing presented in this research work was supported by Fondazione Edmund Mach (FEM), which allowed us to perform the tests in the tree lines of its farm. We also want to thank all the SOLCO team and in particular our colleague Gianluca Demattè who provided his expertise in the data analysis that greatly helped achieving the results.
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Carlino, A., Altomare, L., Darin, M., Visintainer, F., Marchetto, A. (2016). Automotive LIDAR-Based Strategies for Obstacle Detection Application in Rural and Secondary Roads. In: Schulze, T., Müller, B., Meyer, G. (eds) Advanced Microsystems for Automotive Applications 2015. Lecture Notes in Mobility. Springer, Cham. https://doi.org/10.1007/978-3-319-20855-8_8
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DOI: https://doi.org/10.1007/978-3-319-20855-8_8
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