Metaheuristic Strategy in Automatic Robotics Navigation for Patient Care in Hospitals
Journal
Machine Learning Methods in Biomedical Field : Computer-Aided Diagnostics, Healthcare and Biology Applications
ISSN
1860-949X
1860-9503
Publisher
Springer Nature Switzerland
Date Issued
2025
Author(s)
Monroy-Rueda, Irvine J.
Type
text::book::book part
Abstract
This chapter presents a novel approach for developing a global automatic navigation strategy for a mobile robot for patient care into health centers and hospitals. The proposal uses a metaheuristic strategy through the Grey Wolf Optimizer algorithm to find the shortest route between the robot’s starting and patient destination points, while also integrating knowledge of the environment acquired through vision. The global navigation tracking is achieved through the use of Fuzzy Logic Rules to control the robot’s wheel velocity according to its current position and orientation. The proposed strategy was implemented in a virtual robotics environment demonstrating that the approach successfully generated optimal paths for various environments with a minimal number of control points and in a relatively short amount of time. In addition, a simulated hospital room with common furniture and tasks was used to evaluate the performance of the global navigation strategy, demonstrating that the robot could successfully generate a global route and navigate within this environment. ©The authors ©Springer.
Subjects
License
Acceso Restringido
How to cite
Monroy-Rueda, I.J., Moya-Albor, E., Brieva, J., Ponce, H. (2026). Metaheuristic Strategy in Automatic Robotics Navigation for Patient Care in Hospitals. In: Moya-Albor, E., Ponce, H., Brieva, J., Gomez-Coronel, S.L., Torres, D.R. (eds) Machine Learning Methods in Biomedical Field. Studies in Computational Intelligence, vol 1218. Springer, Cham. https://doi.org/10.1007/978-3-031-96328-5_9