Path Planning for Autonomous Articulated Vehicle Based on Improved Goal-Directed Rapid-Exploring Random Tree. (20th May 2020)

• Record Type: Journal Article
• Authors: Xu, Tong; Xu, Yang; Wang, Dong; Chen, Siwei; Zhang, Weigong; Feng, Lihang
• Other Names: Reinoso Oscar Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2020(2020)
• Publication Date: 2020-05-20
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2020/7123164
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : The special steering characteristics and task complexity of autonomous articulated vehicle (AAV) make it often require multiple forward and backward movements during autonomous driving. In this paper, we present a simple yet effective method, named head correction with fixed wheel position (HC-FWP), for the demand of multiple forward and backward movements. The goal-directed rapid-exploring random tree (GDRRT) algorithm is first used to search for a feasible path in the obstacle map, and then, the farthest node search (FNS) algorithm is applied to obtain a series of key nodes, on which HC-FWP is used to correct AAV heading angles. Simulation experiments with Dynapac CC6200 articulated road roller parameters show that the proposed improved goal-directed rapid-exploring random tree (IGDRRT), consisting of GDRRT, FNS, and HC-FWP, can search a feasible path on maps that require the AAV to move back and forth.