FDSPC: Fast and Direct Smooth Path Planning via Continuous Curvature Integration¶
Authors: Zong Chen, Haoluo Shao, Ben Liu, Siyuan Qiao, Yu Zhou, Yiqun Li
Published: 2024 (Conference Paper)
Source: IEEE Robotics and Automation Letters (RA-L)
Algorithm: FDSPC
arXiv: 2405.03281
DOI: 10.1109/LRA.2025.3604729
Summary¶
Proposes FDSPC, a global path planner that directly produces G2 smooth paths via continuous curvature integration. It essentially uses a goal-directed heuristic for selecting (otherwise unspecified) yaw angles at sampled positions, rather than attempting to connect (x, y, yaw) boundary poses directly.
Abstract¶
In recent decades, global path planning of robot has seen significant advancements. Both heuristic search-based methods and probability sampling-based methods have shown capabilities to find feasible solutions in complex scenarios. However, mainstream global path planning algorithms often produce paths with bends, requiring additional smoothing post-processing. In this work, we propose a fast and direct path planning method based on continuous curvature integration. This method ensures path feasibility while directly generating global smooth paths with constant velocity, thus eliminating the need for post-path-smoothing. Furthermore, we compare the proposed method with existing approaches in terms of solution time, path length, memory usage, and smoothness under multiple scenarios. The proposed method is vastly superior to the average performance of state-of-the-art (SOTA) methods, especially in terms of the self-defined S_2 smoothness (mean angle of steering). These results demonstrate the effectiveness and superiority of our approach in several representative environments.
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Tags¶
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Path planning
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Smooth paths
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Curvature continuity
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Heuristic