FDSPC: Fast and Direct Smooth Path Planning via Continuous Curvature Integration

TL;DR

This paper introduces a fast, direct path planning method based on continuous curvature integration that generates globally smooth paths with constant velocity, eliminating the need for post-processing smoothing.

Contribution

It presents a novel path planning approach that ensures smooth, feasible paths directly during planning, outperforming existing methods in speed, smoothness, and resource efficiency.

Findings

Vastly superior in solution time compared to SOTA methods

Produces paths with better smoothness and shorter length

Reduces memory usage and post-processing requirements

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 $\mathcal{S}_2 $ smoothness (mean angle of steering). These results demonstrate the effectiveness and superiority of our approach in several representative environments.