Journal of South China University of Technology (Natural Science Edition) ›› 2021, Vol. 49 ›› Issue (5): 102-110.doi: 10.12141/j.issn.1000-565X.200300

Special Issue: 2021年机械工程

• Mechanical Engineering • Previous Articles     Next Articles

Research on Clonal Selection Algorithm for Multi-Robot Task Allocation and Scheduling

QUAN Yanming HE Yiming   

  1. School of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou 510640, Guangdong, China
  • Received:2020-06-08 Revised:2020-11-26 Online:2021-05-25 Published:2021-04-30
  • Contact: 全燕鸣(1957-),女,教授,博士生导师,主要从事机器视觉、机器人自主导航与路径规划及多机器人任务分配与调度方法研究。 E-mail:meymquan@scut.edu.cn
  • About author:全燕鸣(1957-),女,教授,博士生导师,主要从事机器视觉、机器人自主导航与路径规划及多机器人任务分配与调度方法研究。
  • Supported by:
    Supported by the Characteristic Innovation Projects of Ordinary Colleges and Universities in Guangdong Province (2019KTSCX003) and the Natural Science Foundation of Guangdong Province(2020A1515011503)

Abstract: A clonal selection algorithm (CSA) for multi-robot collaborative scheduling was proposed to solve  the difficulties in controlling and optimizing the task assignment and scheduling of multi-robot in the same period in intelligent manufacturing system. Firstly, the initial conditions of multi-robot task were analyzed. Then taking the task completion as the constraint condition and taking task flow time, single robot maximum cost and multi-robot total cost as the objective function, a mathematical model of multi-robot task allocation and scheduling optimization was constructed. The affinity function was introduced to dynamically change the parameters of clone, mutation and selection, so as to improve the computational efficiency. Finally, the scheduling method was verified by Gantt chart analysis. The results show that the proposed method is stable and feasible. Meanwhile, the experiments show that the clonal selection algorithm has the superiority of fast convergence speed and high calculation accuracy, and can optimize various indicators under complex multi-task conditions.

Key words: intelligent manufacturing system, multi-robot, multi-task allocation, scheduling, clonal selection algorithm

CLC Number: