A Real-Time local path planning method based on SVM for UGV

Publication Type:
Journal Article
Citation:
Boletin Tecnico/Technical Bulletin, 2017, 55 (17), pp. 487 - 499
Issue Date:
2017-11-01
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Path planning is one of essentials of unmanned ground vehicle (UGV). For the case of poor lighting and weather, traditional vision based methods can not extract effective route boundaries to generate reasonable path stably in unstructured road. By ta king advantage of distance-sensing technology (e.g. 64-beam LiDAR), th is paper proposes an efficient real-time path planning approach. In this approach, given grid map fro m 64-bea m LiDAR, obstacles on both sides of the road are regarded as two classes fed to Support Vector Machine (SVM) to generate an initial safe path. During driving, a time weight based least square fitting is adopted to refine path fro m mu ltiple safe paths which will be described by quartic polynomial, providing stable driving route. Co mbined with UGV's state, controls points from the refined path are adopted to generate the final path through Bezier curve fitting. Experiments on real UGV under different road scenario are conducted, showing that the proposed method can obtain stable and reasonable path with promising performance.
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