A curvature-segmentation-based minimum time algorithm for autonomous vehicle velocity planning q

被引:8
作者
Wang, Miao [1 ,3 ]
Liu, Qingshan [2 ,3 ]
Zheng, Yanling [2 ,3 ]
机构
[1] Southeast Univ, Sch Cyber Sci & Engn, Nanjing 210096, Peoples R China
[2] Southeast Univ, Sch Math, Nanjing 210096, Peoples R China
[3] Southeast Univ, Jiangsu Prov Key Lab Networked Collect Intelligen, Nanjing 210096, Peoples R China
基金
中国国家自然科学基金;
关键词
Motion planning; Time-optimal velocity planning; Curvature segmentation; Optimization problems; PSO; UNDERWATER VEHICLES; MOBILE ROBOTS; PATH;
D O I
10.1016/j.ins.2021.02.037
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Velocity planning serves as an important issue in motion planning for autonomous vehicles. The presented paper proposes a novel velocity planning method with minimum moving time on the basis of path curvature which is accomplished in three steps. First, the assigned path is divided into some elementary parts based on the path curvature. Second, the velocity planning is transformed into an unconstrained optimization problem by assuming the velocity of vehicle to be a specific cubic polynomial on every elementary part to avoid a sudden acceleration in path switching. Finally, we use a modified projection particle swarm optimization (PPSO) algorithm to obtain the time-optimal velocity profile. The proposed method can generate a smooth time-optimal velocity profile while considering all possible relevant constraints. Three examples are provided on different types of path to demonstrate that the final velocity profile is efficient to avoid the sudden acceleration change. Furthermore, the modified PPSO algorithm in this paper is used to solve the optimization problem with high dimensional variables when its upper bound is known, which can not be achieved by the general PPSO algorithm. (c) 2021 Elsevier Inc. All rights reserved.
引用
收藏
页码:248 / 261
页数:14
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