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浙江大学学报(工学版)
浙江大学学报(工学版)  2025, Vol. 59 Issue (2): 375-383    DOI: 10.3785/j.issn.1008-973X.2025.02.015
机械工程、能源工程     
护工-机器人协作养老情境下的多任务分配框架
李勇1(),王跃1,柳富强2,孙柏青1,李恺如1
1. 沈阳工业大学 电气工程学院，辽宁 沈阳 110870
2. 大连医科大学附属第一医院，辽宁 大连 116021
Multi-task allocation framework in context of caregiver-robot collaborative elderly care
Yong LI1(),Yue WANG1,Fuqiang LIU2,Baiqing SUN1,Kairu LI1
1. School of Electrical Engineering, Shenyang University of Technology, Shenyang 110870, China
2. The First Affiliated Hospital of Dalian Medical University, Dalian 116021, China
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摘要：

为了兼顾护工和老人的主观感受，提出考虑护工疲劳度和老人满意度的多人机协作任务分配框架. 考虑护工执行任务前的休息时长、护工和老人之间的好感度、任务难度等因素，建立护工疲劳度的数学模型，结合老人满意度建立多人机协作任务分配多目标优化模型. 结合养老情境下常见任务的特点，提出二维双约束编码及其合理初始化和更新方法. 基于该编码，采用多目标进化算法对多目标优化模型进行求解. 根据min-max与max-min原则，在Pareto最优解集中确定最终的任务执行方案，以防止出现个体护工疲劳度极大或个体老人满意度极小的情况. 仿真结果表明，在提出的养老情境下，“多护工-多机器人”协作的多任务分配框架能够在完成多护工-多机器人团队任务分配的同时，兼顾护工疲劳度和老人满意度、护工总体和个体之间、老人总体和个体之间的平衡.
关键词： 养老情境;  多任务分配;  护工疲劳度;  多目标优化    
Abstract:

A multi-human-robot collaboration task allocation framework considering both caregiver’s fatigue and elderly satisfaction was proposed in order to balance the subjective feelings of caregivers and elderly people. A mathematical model of caregiver’s fatigue was established by considering factors such as caregiver’s rest duration before task execution, the rapport between caregivers and elderly people, and task difficulty. A multi-objective optimization model for multi-human-robot collaboration task allocation was developed combined with elderly satisfaction. A two-dimensional double-constraint encoding method and its reasonable initialization and updating methods were proposed based on the characteristics of common tasks in elderly care scenarios. A multi-objective evolutionary algorithm was employed to solve the multi-objective optimization model by using this encoding. The final task execution plan was determined from the Pareto optimal solution set according to the min-max and max-min principles in order to prevent situations where individual caregivers experience extreme fatigue or individual elderly people have extremely low satisfaction. The simulation results demonstrate that the multi-task allocation framework for ‘multiple caregivers and multiple robots’ collaboration can achieve task allocation within a multi-caregiver and multi-robot team in the proposed elderly care scenario while balancing caregiver’s fatigue and elderly satisfaction, as well as maintaining a balance between the overall and individual caregivers, and between the overall and individual elderly people.
Key words: elderly care scenario    multi-task allocation    caregiver’s fatigue    multi-objective optimization
收稿日期: 2023-12-28 出版日期: 2025-02-11
CLC:  TP 18  
基金资助: 辽宁省兴辽英才计划资助项目（XLYC2203104）.
作者简介: 李勇（1980—），男，教授，博士，从事系统建模与多目标优化和机器学习等的研究. orcid.org/0000-0002-3098-6363. E-mail：liyong@sut.edu.cn
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李勇
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引用本文:

李勇,王跃,柳富强,孙柏青,李恺如. 护工-机器人协作养老情境下的多任务分配框架[J]. 浙江大学学报(工学版), 2025, 59(2): 375-383.

Yong LI,Yue WANG,Fuqiang LIU,Baiqing SUN,Kairu LI. Multi-task allocation framework in context of caregiver-robot collaborative elderly care. Journal of ZheJiang University (Engineering Science), 2025, 59(2): 375-383.

链接本文:

https://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2025.02.015    或    https://www.zjujournals.com/eng/CN/Y2025/V59/I2/375

图 1  TAV示意图
图 2  任务执行方案编码的迭代交叉方式
图 3  AG-子任务时间同步处理的流程图
图 4  虚拟养老情境图
图 5  McmrTAF的任务执行方案的Pareto解集
图 6  护工和老人的主观感受情况及最终方案的对比图：2种执行方案相差较大的情况
图 7  护工和老人的主观感受情况及最终方案的对比图：2种执行方案相同的情况
图 8  护工和老人的主观感受情况及最终方案的对比图：2种执行方案相近的情况
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