Abstract
The aging population and expectations for nursing care robots increased significantly recently. We focused on mobile assistive robots. When various types of robots introduced into nursing homes, they should be assigned appropriately to fulfill the demands of multiple older adults. We consider a scenario wherein multiple older adults press the nurse-call button simultaneously. Various robots are then assigned such that each older person is served by one robot. We solved the problem of assigning mobile assistive robots using matching theory. Assignments based on matching theory consider the nursing home manager’s interest, tasks’ urgency, and older adult’s preferences in the robots. Specifically, we proposed an assignment method for total optimization by evaluating the variables. Numerical simulations confirmed that the average waiting time of the residents with highly urgent tasks was reduced. The robot type, years of use, and usage fees matched older People’s preferences.
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This work was presented in part at the joint symposium of the 27th International Symposium on Artificial Life and Robotics, the 7th International Symposium on BioComplexity, and the 5th International Symposium on Swarm Behavior and Bio-Inspired Robotics (Online, January 25–27, 2022).
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Shimada, N., Cao, W. & Zhang, Y. Optimal assignment method for mobile assistive robots using matching theory. Artif Life Robotics 28, 199–207 (2023). https://doi.org/10.1007/s10015-022-00825-z
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DOI: https://doi.org/10.1007/s10015-022-00825-z