Systematic review of machine learning strategies for adapting collaborative robots to human body size variations
Article Sidebar
Main Article Content
Abstract
This systematic review examines the adaptation of collaborative robots (cobots) to enhance human–robot collaboration (HRC) by addressing ergonomic challenges arising from human body size variations. Following PRISMA guidelines, we comprehensively searched peer-reviewed studies from 2021 onward in Scopus and Google Scholar. Methods were synthesized and methodological strengths and weaknesses evaluated. Keyword analysis reveals growing interdisciplinary integration of ergonomics, artificial intelligence, and collaborative robotics. The findings indicate that future research should prioritize the development of real-time adaptive systems capable of continuous posture monitoring, comfort improvement, and enhanced worker safety in dynamic industrial environments.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
References
Colim A, Faria C, Cunha J, Oliveira J, Sousa N, Rocha LA. Physical ergonomic improvement and safe design of an assembly workstation through collaborative robotics. Safety. 2021;7(1). https://doi.org/10.3390/safety7010014
Das B, Sengupta AK. Industrial workstation design: A systematic ergonomics approach. Appl Ergon. 1996;27(3):157–63. https://doi.org/10.1016/0003-6870(96)00008-7
Martins V, Cerqueira SM, Balcells M, Edelman ER, Santos CP. A Human-Sensitive Controller: Adapting to Human Ergonomics and Physical Constraints via Reinforcement Learning. arXiv preprint arXiv:2504.10102 2025; https://doi.org/10.48550/arXiv.2504.10102
Yang ST, Park MH, Jeong BY. Types of manual materials handling (MMH) and occupational incidents and musculoskeletal disorders (MSDs) in motor vehicle parts manufacturing (MVPM) industry. Int J Ind Ergon. 2020;77:102954. https://doi.org/10.1016/j.ergon.2020.102954
Kim W, Lorenzini M, Balatti P, Nguyen PDH, Pattacini U, Tikhanoff V, et al. Adaptable workstations for human-robot collaboration: A reconfigurable framework for improving worker ergonomics and productivity. IEEE Robot Autom Mag 2019;26:14–26. https://doi.org/10.1109/MRA.2018.2890460
Boschetti G, Faccio M, Granata I. Human-centered design for productivity and safety in collaborative robots cells: A new methodological approach. Electronics. 2022;12(1):167. https://doi.org/10.3390/electronics12010167
Deutsches Institut für Normung. DIN 33402-2: Ergonomics – Human body dimensions – Part 2: Values [Internet]. DIN media2005; Available from: https://www.beuth.de
Villani V, Pini F, Leali F, Secchi C. Survey on human–robot collaboration in industrial settings: Safety, intuitive interfaces and applications. Mechatronics. 2018;55:248–66. https://doi.org/10.1016/j.mechatronics.2018.02.009
Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009 Jul;6(7):e1000097. https://doi.org/10.1016/j.ijsu.2010.02.007
Meregalli Falerni M, Pomponi V, Karimi HR, Lavit Nicora M, Dao LA, Malosio M, et al. A framework for human–robot collaboration enhanced by preference learning and ergonomics. Robot Comput Integr Manuf. 2024;89:102781. https://doi.org/10.1016/j.rcim.2024.102781
Kim W, Lorenzini M, Balatti P, Nguyen PDH, Pattacini U, Tikhanoff V, et al. Adaptable workstations for human-robot collaboration: A reconfigurable framework for improving worker ergonomics and productivity. IEEE Robot Autom Mag. 2019;26(3):14–26. https://doi.org/10.1109/MRA.2018.2890460
