A Time-Space Network Model for Collision-free Routing of Planar Motions in a Multi-Robot Station

Journal Article (2020)
Author(s)

J Xin (Zhengzhou University)

Chuang Meng (Zhengzhou University)

F. Schulte (TU Delft - Transport Engineering and Logistics)

Jinzhu Peng (Zhengzhou University)

Yanhong Liu (Zhengzhou University)

R.R. Negenborn (TU Delft - Transport Engineering and Logistics)

Research Group
Transport Engineering and Logistics
Copyright
© 2020 J. Xin, Chuang Meng, F. Schulte, Jinzhu Peng, Yanhong Liu, R.R. Negenborn
DOI related publication
https://doi.org/10.1109/TII.2020.2968099
More Info
expand_more
Publication Year
2020
Language
English
Copyright
© 2020 J. Xin, Chuang Meng, F. Schulte, Jinzhu Peng, Yanhong Liu, R.R. Negenborn
Research Group
Transport Engineering and Logistics
Issue number
10
Volume number
16
Pages (from-to)
6413-6422
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

This article investigates a new collision-free routing problem of a multirobot system. The objective is to minimize the cycle time of operation tasks for each robot while avoiding collisions. The focus is set on the operation of the end-effector and its connected joint, and the operation is projected onto a circular area on the plane. We propose to employ a time-space network (TSN) model that maps the robot location constraints into the route planning framework, leading to a mixed integer programming (MIP) problem. A dedicated genetic algorithm is proposed for solving this MIP problem and a new encoding scheme is designed to fit the TSN formulation. Simulation experiments indicate that the proposed model can obtain the collision-free route of the considered multirobot system. Simulation results also show that the proposed genetic algorithm can provide fast and high-quality solutions, compared to two state-of-the-art commercial solvers and a practical approach.

Files

A_Time_Space_Network_Model_for... (pdf)
(pdf | 2.97 Mb)
- Embargo expired in 22-07-2020
License info not available