Abstract
The navigation problem of autonomous vehicles in unstructured environments entails the ability of autonomous vehicle to plan an obstacle-free path in real-time between a sequence of waypoints. While there are several path planners in the literature based on optimization, sampling, and geometry, none of them are designed considering the most commonly used sensors, which currently utilize polar coordinates such as LIDAR and RADAR. Inspired by that, this work proposes an algorithm based on computational geometry to path planning step for autonomous vehicle navigation in unstructured environments. The proposed algorithm was evaluated in simulation and its results were compared following the BARN standardized metrics with classical methods. The proposed method achieves the lowest processing time whilst maintaining comparable performance results on the spatial-related metrics. It also outperforms the others on the dispersion metric, suggesting it is a more robust method with more planning options for complex environments.
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Acknowledgments
This work was supported by the CAPES/FAPES (process: 2021-2S6CD, no FAPES 132/2021) in PDPG (Programa de Desenvolvimento da Pós-Graduação - Parcerias Estratégicas nos Estados).
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Baumgarten, A.F., Resendo, L.C., Forechi, A. (2024). Parallel Curves Path Planning Based on Tangent Segments to Concentric Circles. In: Marques, L., Santos, C., Lima, J.L., Tardioli, D., Ferre, M. (eds) Robot 2023: Sixth Iberian Robotics Conference. ROBOT 2023. Lecture Notes in Networks and Systems, vol 976. Springer, Cham. https://doi.org/10.1007/978-3-031-58676-7_21
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