Research on Coupled Task Allocation and Scheduling of Multi-type Robots

Xingkai Wang, Zichao Xing, Weimin Wu, Xinyu Chen
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Abstract

Task allocation problem and scheduling problem have always been hot topics in the robotics research field. Both of them can be divided into many categories. Among all these categories, coupled task allocation and scheduling problem (CTASP) is a quite difficult problem, especially for of multi-type robots. However, few researches are conducted on this area. Usually, the CTASP is studied for multi-type robots with fixed execution sequence in the reported literature. However, this paper will study the CTASP for multi-type robots with flexible execution sequence. A two-dimension genetic algorithm (TDGA) is designed to solve this type of problem, combined with rank minimal heuristic (RMH) algorithm to provide an elite strategy. The simulation experiment proves that TDGA can solve this kind of problems efficiently, and the efficiency of hybrid genetic algorithm has been further improved.
多类型机器人耦合任务分配与调度研究
任务分配问题和调度问题一直是机器人领域的研究热点。两者都可以分为许多类别。其中,耦合任务分配与调度问题(CTASP)是一个相当困难的问题,特别是对于多类型机器人而言。然而,这方面的研究却很少。文献中通常对多类型机器人固定执行顺序的CTASP进行研究。然而,本文将研究具有柔性执行顺序的多类型机器人的CTASP。设计了一种二维遗传算法(TDGA)来解决这类问题,并结合最小秩启发式算法(RMH)来提供精英策略。仿真实验证明,TDGA可以有效地解决这类问题,并进一步提高了混合遗传算法的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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