Path planning with fractional potential fields for autonomous vehicles

被引：21

作者：

Moreau, Julien ^{[1
,3
]}

Melchior, Pierre ^{[1
]}

Victor, Stephane ^{[1
]}

Aioun, Francois ^{[2
]}

Guillemard, Franck ^{[2
]}

机构：

[1] Univ Bordeaux, Bordeaux IPN, IMS UMR CNRS 5218, 351 Cours Liberat, F-33405 Talence, France

[2] PSA Grp, Chemin Gisy, Velizy Villacoublay, France

[3] PSA Grp IMS Bordeaux, OpenLab, Bordeaux, France

来源：

IFAC PAPERSONLINE | 2017年 / 50卷 / 01期

关键词：

Path planning; automotive; autonomous vehicle; potential field; fractional potential field;

D O I：

10.1016/j.ifacol.2017.08.2076

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Path planning is an essential stage for mobile robot control. It is more newsworthy than ever in the automotive context and especially for autonomous vehicle. Also, path planning methods need to be adaptive regarding life situations, traffic and obstacle crossing. In this paper, potential field methods are proposed to cope with these constraints and autonomous vehicles are considered equipped with all necessary sensors for obstacle detection. In this way, Ge&Cui's attractive potential field and fractional attractive potential field have been adapted to the context of autonomous vehicles. In this way, this latter method ensures better stability degree robustness with controlled vehicle acceleration. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

引用

页码：14533 / 14538

页数：6

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