arrow
Return

Coordination of multiple AGVs: a quadratic optimization method

delete2018-04-07
delete37
PRE
AI
V
Valerio Digani
M
M. Ani Hsieh
L
Lorenzo Sabattini *
C
Cristian Secchi
DOI:10.1007/s10514-018-9730-9delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
This paper presents an optimization strategy to coordinate a fleet of Automated Guided Vehicles (AGVs) traveling on ad-hoc pre-defined roadmaps. Specifically, the objective is to maximize traffic throughput of AGVs navigating in an automated warehouse by minimizing the time AGVs spend negotiating complex traffic patterns to avoid collisions with other AGVs. In this work, the coordination problem is posed as a Quadratic Program where the optimization is performed in a centralized manner. The proposed method is validated by means of simulations and experiments for different industrial warehouse scenarios. The performance of the proposed strategy is then compared with a recently proposed decentralized coordination strategy that relies on local negotiations for shared resources. The results show that the proposed coordination strategy successfully maximizes vehicle throughput and significantly minimizes the time vehicles spend negotiating traffic under different scenarios.
Keywords:
Multi-robot coordination
Quadratic optimization
AGV systems
Path planning
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Autonomous Robots cover
Autonomous Robots
IF:
4.3
Papers:
1.7K
Citations:
5.0K

Organization

U
universita di modena e reggio emilia
Scholars:
1.6W
Papers: 1.2W
Citations: 12
U
university of pennsylvania
Scholars:
9.2W
Papers: 7.8W
Citations: 153