Exact Wavefront Propagation for Globally Optimal One-to-All Path Planning on 2D Cartesian Grids

被引:0
|
作者
Ibrahim, Ibrahim [1 ,2 ]
Gillis, Joris [1 ,2 ]
Decre, Wilm [1 ,2 ]
Swevers, Jan [1 ,2 ]
机构
[1] Katholieke Univ Leuven, Dept Mech Engn, MECO Res Team, B-3000 Leuven, Belgium
[2] Flanders Make KU Leuven, B-3000 Leuven, Belgium
来源
IEEE ROBOTICS AND AUTOMATION LETTERS | 2024年 / 9卷 / 11期
关键词
Path planning; Complexity theory; Accuracy; Heuristic algorithms; Three-dimensional displays; Benchmark testing; Partial differential equations; Motion and path planning; path planning for multiple robots or agents; computational geometry; FAST MARCHING METHOD; LEVEL SET METHOD; EIKONAL EQUATION; ALGORITHM;
D O I
10.1109/LRA.2024.3460409
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
This letter introduces an efficient O(n) compute and memory complexity algorithm for globally optimal path planning on 2D Cartesian grids. Unlike existing marching methods that rely on approximate discretized solutions to the Eikonal equation, our approach achieves exact wavefront propagation by pivoting the analytic distance function based on visibility. The algorithm leverages a dynamic-programming subroutine to efficiently evaluate visibility queries. Through benchmarking against state-of-the-art any-angle path planners, we demonstrate that our method outperforms existing approaches in both speed and accuracy, particularly in cluttered environments. Notably, our method inherently provides globally optimal paths to all grid points, eliminating the need for additional gradient descent steps per path query. The same capability extends to multiple starting positions. We also provide a greedy version of our algorithm as well as open-source C++ implementation of our solver.
引用
收藏
页码:9431 / 9437
页数:7
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