{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T05:09:11Z","timestamp":1783573751952,"version":"3.55.0"},"reference-count":31,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2025,4,24]],"date-time":"2025-04-24T00:00:00Z","timestamp":1745452800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Shanghai Action Plan for Science, Technology and Innovation","award":["24YL1900900"],"award-info":[{"award-number":["24YL1900900"]}]},{"name":"Shanghai Action Plan for Science, Technology and Innovation","award":["CJGJZD20230724094002005"],"award-info":[{"award-number":["CJGJZD20230724094002005"]}]},{"name":"Shenzhen Science and Technology Program","award":["24YL1900900"],"award-info":[{"award-number":["24YL1900900"]}]},{"name":"Shenzhen Science and Technology Program","award":["CJGJZD20230724094002005"],"award-info":[{"award-number":["CJGJZD20230724094002005"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Bioengineering"],"abstract":"<jats:p>Nursing robots are designed to serve users, and their ability to interact with humans, as well as to make task-related decisions and decompositions based on such interactions, is a fundamental prerequisite for autonomous execution of nursing tasks. Large language models offer an effective approach to facilitating human\u2013robot interaction. However, their global perspective can lead to confusion or reduced precision when coordinating the execution of tasks by a dual-arm robot, often generating execution sequences that are inconsistent with real-world conditions. To address this challenge, this study proposes a multi-agent framework, wherein each arm of the nursing robot is conceptualized as an independent agent. Through the application of geometric constraints, these agents maintain appropriate relative positional relationships and achieve coordinated collaboration via a large language model. This approach enhances the task planning capabilities of the robot and improves its efficiency in delivering nursing services.<\/jats:p>","DOI":"10.3390\/bioengineering12050448","type":"journal-article","created":{"date-parts":[[2025,4,24]],"date-time":"2025-04-24T10:17:16Z","timestamp":1745489836000},"page":"448","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["The Multi-Agentization of a Dual-Arm Nursing Robot Based on Large Language Models"],"prefix":"10.3390","volume":"12","author":[{"given":"Chuanhong","family":"Fang","sequence":"first","affiliation":[{"name":"Academy for Engineering & Technology, Fudan University, Shanghai 200433, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-7738-5698","authenticated-orcid":false,"given":"Xiaotian","family":"Yue","sequence":"additional","affiliation":[{"name":"College of Computer and Control Engineering, Qiqihar University, Qiqihar 161000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-8706-5647","authenticated-orcid":false,"given":"Zhendong","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence & Data Science, Hebei University of Technology, Tianjin 300130, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shijie","family":"Guo","sequence":"additional","affiliation":[{"name":"Academy for Engineering & Technology, Fudan University, Shanghai 200433, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,4,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"107","DOI":"10.5582\/bst.2022.01068","article-title":"Current State of Care for the Elderly in China in the Context of an Aging Population","volume":"16","author":"Bao","year":"2022","journal-title":"Biosci. Trends"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"590","DOI":"10.1111\/jnu.12424","article-title":"Robotics in Nursing: A Scoping Review","volume":"50","author":"Maalouf","year":"2018","journal-title":"J. Nurs. Scholarsh."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Soriano, G.P., Yasuhara, Y., Ito, H., Matsumoto, K., Osaka, K., Kai, Y., Locsin, R., Schoenhofer, S., and Tanioka, T. (2022). Robots and Robotics in Nursing. Healthcare, 10.","DOI":"10.3390\/healthcare10081571"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"41","DOI":"10.2174\/2212797611666180306124236","article-title":"Research Progress and Prospect of Nursing Robot","volume":"11","author":"Jiang","year":"2018","journal-title":"Recent Pat. Mech. Eng."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"17298806241249848","DOI":"10.1177\/17298806241249848","article-title":"Human-Robot Mechanics Model Using Hip Torque Identification with a Dual-Arm Nursing-Care Transfer Robot","volume":"21","author":"Yang","year":"2024","journal-title":"Int. J. Adv. Robot. Syst."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Zhao, D., Sun, X., Shan, B., Yang, Z., Yang, J., Liu, H., Jiang, Y., and Yokoi, H. (2023). Research Status of Elderly-Care Robots and Safe Human-Robot Interaction Methods. Front. Neurosci., 17.","DOI":"10.3389\/fnins.2023.1291682"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"104643","DOI":"10.1016\/j.robot.2024.104643","article-title":"Modelling and Identification Methods for Simulation of Cable-Suspended Dual-Arm Robotic Systems","volume":"175","author":"Selvaggio","year":"2024","journal-title":"Robot. Auton. Syst."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"678","DOI":"10.1016\/j.ins.2022.10.002","article-title":"Empirical Prior Based Probabilistic Inference Neural Network for Policy Learning","volume":"615","author":"Li","year":"2022","journal-title":"Inf. Sci."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Li, J., Wang, C., and Deng, H. (2023). Hybrid Nursing Robot Based on Humanoid Pick-Up Action: Safe Transfers in Living Environments for Lower Limb Disabilities. Actuators, 12.","DOI":"10.3390\/act12120438"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Zhang, L., Wang, S., and Miao, X. (2019, January 8\u201311). Workspace Simulation and Analysis of a Dual-Arm Nursing Robot. Proceedings of the 12th International Conference on Intelligent Robotics and Applications (ICIRA 2019), Shenyang, China. Part VI.","DOI":"10.1007\/978-3-030-27529-7_3"},{"key":"ref_11","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, \u0141., and Polosukhin, I. (2017, January 4\u20139). Attention is All you Need. Proceedings of the Advances in Neural Information Processing Systems, Long Beach, CA, USA."},{"key":"ref_12","unstructured":"Devlin, J., Chang, M.W., Lee, K., and Toutanova, K. (2019, January 2\u20137). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT), Minneapolis, MN, USA."},{"key":"ref_13","first-page":"1","article-title":"PaLM: Scaling Language Modeling with Pathways","volume":"24","author":"Chowdhery","year":"2023","journal-title":"J. Mach. Learn. Res."},{"key":"ref_14","unstructured":"Ahn, M., Brohan, A., Brown, N., Chebotar, Y., Cortes, O., David, B., Finn, C., Fu, C., Gopalakrishnan, K., and Hausman, K. (2022). Do as I Can, Not as I Say: Grounding Language in Robotic Affordances. arXiv."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1087","DOI":"10.1007\/s10514-023-10139-z","article-title":"TidyBot: Personalized Robot Assistance with Large Language Models","volume":"47","author":"Wu","year":"2023","journal-title":"Auton. Robot."},{"key":"ref_16","unstructured":"Wu, J., Chong, W., Holmberg, R., Prasad, A., Gao, Y., Khatib, O., Song, S., Rusinkiewicz, S., and Bohg, J. (2024). TidyBot++: An Open-Source Holonomic Mobile Manipulator for Robot Learning. arXiv."},{"key":"ref_17","unstructured":"Huang, W., Wang, C., Zhang, R., Li, Y., Wu, J., and Fei-Fei, L. (2023). Voxposer: Composable 3D Value Maps for Robotic Manipulation with Language Models. arXiv."},{"key":"ref_18","first-page":"1877","article-title":"Language Models are Few-Shot Learners","volume":"33","author":"Brown","year":"2020","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_19","first-page":"24824","article-title":"Chain-of-Thought Prompting Elicits Reasoning in Large Language Models","volume":"35","author":"Wei","year":"2022","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Singh, I., Blukis, V., Mousavian, A., Goyal, A., Xu, D., Tremblay, J., Fox, D., Thomason, J., and Garg, A. (June, January 29). ProgPrompt: Generating Situated Robot Task Plans Using Large Language Models. Proceedings of the 2023 IEEE International Conference on Robotics and Automation (ICRA), London, UK.","DOI":"10.1109\/ICRA48891.2023.10161317"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Liang, J., Huang, W., Xia, F., Xu, P., Hausman, K., Ichter, B., Florence, P., and Zeng, A. (June, January 29). Code as Policies: Language Model Programs for Embodied Control. Proceedings of the 2023 IEEE International Conference on Robotics and Automation (ICRA), London, UK.","DOI":"10.1109\/ICRA48891.2023.10160591"},{"key":"ref_22","unstructured":"Chen, M., Tworek, J., Jun, H., Yuan, Q., Pinto, H.P.D.O., Kaplan, J., Edwards, H., Burda, Y., Joseph, N., and Brockman, G. (2021). Evaluating Large Language Models Trained on Code. arXiv."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Mandi, Z., Jain, S., and Song, S. (2024, January 2\u20136). Roco: Dialectic Multi-Robot Collaboration with Large Language Models. Proceedings of the 2024 IEEE International Conference on Robotics and Automation (ICRA), Osaka, Japan.","DOI":"10.1109\/ICRA57147.2024.10610855"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Liang, T., He, Z., Jiao, W., Wang, X., Wang, Y., Wang, R., Yang, Y., Shi, S., and Tu, Z. (2023). Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate. arXiv.","DOI":"10.18653\/v1\/2024.emnlp-main.992"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Chatzea, V.E., Logothetis, I., Kalogiannakis, M., Rovithis, M., and Vidakis, N. (2024). Digital Educational Tools for Undergraduate Nursing Education: A Review of Serious Games, Gamified Applications and Non-Gamified Virtual Reality Simulations\/Tools for Nursing Students. Information, 15.","DOI":"10.3390\/info15070410"},{"key":"ref_26","first-page":"51991","article-title":"CAMEL: Communicative Agents for \u201cMind\u201d Exploration of Large Language Model Society","volume":"36","author":"Li","year":"2023","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_27","unstructured":"Chan, C.M., Chen, W., Su, Y., Yu, J., Xue, W., Zhang, S., Fu, J., and Liu, Z. (2023). Chateval: Towards Better LLM-Based Evaluators through Multi-Agent Debate. arXiv."},{"key":"ref_28","unstructured":"Schaal, S., Peters, J., Nakanishi, J., and Ijspeert, A. (2003, January 27\u201331). Control, Planning, Learning, and Imitation with Dynamic Movement Primitives. Proceedings of the Workshop on Bilateral Paradigms on Humans and Humanoids: IEEE International Conference on Intelligent Robots and Systems (IROS), Las Vegas, NV, USA."},{"key":"ref_29","unstructured":"GLM Team, Zeng, A., Xu, B., Wang, B., Zhang, C., Yin, D., Zhang, D., Rojas, D., Feng, G., and Zhao, H. (2024). ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools. arXiv."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1007\/s12206-019-1234-9","article-title":"Kinematics and Dynamics Analysis of the 3 P US-P RU Parallel Mechanism Module Designed for a Novel 6-DOF Gantry Hybrid Machine Tool","volume":"34","author":"Lu","year":"2020","journal-title":"J. Mech. Sci. Technol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1687814020913667","DOI":"10.1177\/1687814020913667","article-title":"Minimum-Jerk Trajectory Planning Pertaining to a Translational 3-Degree-of-Freedom Parallel Manipulator through Piecewise Quintic Polynomials Interpolation","volume":"12","author":"Lu","year":"2020","journal-title":"Adv. Mech. Eng."}],"container-title":["Bioengineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2306-5354\/12\/5\/448\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T17:20:58Z","timestamp":1760030458000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2306-5354\/12\/5\/448"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,24]]},"references-count":31,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2025,5]]}},"alternative-id":["bioengineering12050448"],"URL":"https:\/\/doi.org\/10.3390\/bioengineering12050448","relation":{},"ISSN":["2306-5354"],"issn-type":[{"value":"2306-5354","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,4,24]]}}}