A reinforcement learning-based optimization method for task allocation of agricultural multi-robots clusters

doi:10.1016/j.compeleceng.2024.109752

	A reinforcement learning-based optimization method for task allocation of agricultural multi-robots clusters
	Lu, Zaiwang 1,2; Wang, Yancong 1; Dai, Feng 1; Ma, Yike 1; Long, Long 1; Zhao, Zixu 1,2; Zhang, Yucheng 1; Li, Jintao 1
	2024-12-01
发表期刊	COMPUTERS & ELECTRICAL ENGINEERING (IF:1.747[JCR-2017],1.781[5-Year])
ISSN	0045-7906
卷号	120 页码:15
摘要	The Agricultural multi-robot task allocation (AMRTA) can allocate the optimal operation sequence for the cluster of agricultural robots and improve overall operational efficiency, which is an important research direction for the development of intelligent agriculture. In this paper, we first analyzed the practical requirements of multi-robot task allocation in agriculture and reformulate it as Node Workload-Constrained Multi Traveling Salesman Problem (NWCMTSP), aiming to minimize the maximum operating time of sub-robots while ensuring a balanced distribution of workload as much as possible. Then, we implemented path planning algorithm required for task allocation and constructed an objective function based on it; we also constructed a graph structure containing workloads of nodes, used graph neural networks to obtain node feature information, and propose a Reinforcement Learning-based Attention Mechanism Policy Optimization Network (NWC-APONet) method to find the optimal allocation scheme. Finally, our model evaluated using real agricultural datasets, i.e., the TSPLIB public dataset and random datasets. Experiments results demonstrate that NWC-APONet achieves superior task allocation, which prove our model's practical applicability and effectiveness in AMRTA.
关键词	Graph neural network Multi-robot systems Agricultural task allocation Multiple traveling salesmen problem Reinforcement learning
DOI	10.1016/j.compeleceng.2024.109752
收录类别	SCI
语种	英语
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Hardware & Architecture ; Computer Science, Interdisciplinary Applications ; Engineering, Electrical & Electronic
WOS记录号	WOS:001343530400001
出版者	PERGAMON-ELSEVIER SCIENCE LTD
引用统计	被引频次：1[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/39504
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Dai, Feng
作者单位	1.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Lu, Zaiwang,Wang, Yancong,Dai, Feng,et al. A reinforcement learning-based optimization method for task allocation of agricultural multi-robots clusters[J]. COMPUTERS & ELECTRICAL ENGINEERING,2024,120:15.
APA	Lu, Zaiwang.,Wang, Yancong.,Dai, Feng.,Ma, Yike.,Long, Long.,...&Li, Jintao.(2024).A reinforcement learning-based optimization method for task allocation of agricultural multi-robots clusters.COMPUTERS & ELECTRICAL ENGINEERING,120,15.
MLA	Lu, Zaiwang,et al."A reinforcement learning-based optimization method for task allocation of agricultural multi-robots clusters".COMPUTERS & ELECTRICAL ENGINEERING 120(2024):15.