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research-article

A Fast Algorithm on Minimum-Time Scheduling of an Autonomous Ground Vehicle using a Traveling Salesman Framework

[+] Author and Article Information
Soovadeep Bakshi

Dept. of Mechanical Engineering, The University of Texas at Austin, Austin, Texas 78712
soovadeep.bakshi@utexas.edu

Zeyu Yan

Dept. of Mechanical Engineering, The University of Texas at Austin, Austin, Texas 78712
zyyan@utexas.edu

Dongmei Chen

Dept. of Mechanical Engineering, The University of Texas at Austin, Austin, Texas 78712
dmchen@me.utexas.edu

Qiang Qian

Dalian Auto Tech, Dalian, Liaoning 116051, China
qianqiang@dlautotech.com

Yinan Chen

Dalian Auto Tech, Dalian, Liaoning 116051, China
chenyinan@dlautotech.com

1Corresponding author.

ASME doi:10.1115/1.4040665 History: Received October 09, 2017; Revised June 20, 2018

Abstract

Manufacturing automation, especially through implementation of autonomous ground vehicle (AGV) technology, has been under intensive study due to increased productivity and reduced variations. The objective of this paper is to present an algorithm on scheduling of an AGV that traverses desired locations on a manufacturing floor. Although many algorithms have been developed to achieve this objective, most of them rely on exhaustive search, which is time-consuming. A novel two-step algorithm that generates 'good', but not necessarily optimal, solutions for relatively large data sets (~1000 points) is proposed, taking into account time constraints. A trade-off analysis of computational expense versus algorithm performance is discussed. The algorithm enables the AGV to find a tour which is as good as possible within the time constraint, using which it can travel through all given coordinates before returning to the starting location or a specified end-point. Compared to exhaustive search methods, this algorithm generates results within a stipulated computation time of thirty seconds on a laptop PC.

Copyright (c) 2018 by ASME
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