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innovation has the potential to transform healthcare robot think about. It might be a bit hard for computers to use be-
mobility, making operations smoother and more efficient. cause it is a bit complex, and it might not work perfectly
in real-life situations. Moreover, it might not work well in
However, it is crucial to consider potential limitations, different types of places.
including the need for accurate dynamic modeling, sensor
data, and challenges in real-world hospital integration. Further In a healthcare surface disinfection robot study [23], I. T.
testing in various hospital settings and conditions is necessary Kurniawan and W. Adiprawita created three key modules: one
to assess its practicality. for finding its location (Augmented Monte Carlo Localiza-
tion), one for planning its path (Rapidly Exploring Random
A new path-planning algorithm was introduced in [19] for Tree*), and another for covering surfaces (Spanning Tree Cov-
autonomous electric wheelchairs in hospitals, aiming to ensure erage). These robots can autonomously disinfect surfaces
patient safety by considering constraints on body acceleration using ultraviolet-C lamps, achieving high sterilization rates
and navigating appropriate routes within healthcare facilities. without human involvement. The robot’s intelligent decision-
This algorithm takes into account wheelchair characteristics, making ensures safety by minimizing infection and radiation
user input, and wheel behavior, making it adaptable to differ- risks. Nevertheless, concerns remain, including limited real-
ent wheelchair systems. Through thorough numerical simula- world testing and potential performance variations based on
tions and testing in real hospital environments, the algorithm usage conditions.
proves its ability to meet body acceleration constraints and
find suitable paths within hospitals. This promising solution In recent research [24], S. Wan, Z. Gu, and Q. Ni explored
enhances the performance of autonomous electric wheelchairs the latest developments in mobile healthcare robots with a
in healthcare settings. focus on strong and fast communication. They worked on
improving tasks that need quick responses and a lot of commu-
In a university research project, D. P. Romero-Mart´i, J. nication by offloading some tasks, making healthcare robots
I. Nu´nez-Varela, C. Soubervielle-Montalvo, and A. Orozco- more effective. They split the robot’s functions into edge
de-la-Paz [20]. introduce a service robot that uses a map and core tasks, emphasizing technologies like human-robot
of a building and reinforcement learning to learn the best interaction, navigation, and AI. They also tackled challenges
routes between locations. They incorporated a Roomba robot in wireless communication for these robots and highlighted
and created a user-friendly control system. This research has AI’s vital role in ensuring safety and reliability in health-
promising implications for using service robots in various care services. This approach benefits healthcare service users
settings like homes, hospitals, and offices, where they can by enabling quick-response, communication-intensive tasks.
assist with a variety of tasks. However, limitations exist, However, it necessitates robust communication and advanced
such as potential inaccuracies in the robot’s maps and its AI for managing radio signals, movement, and service deliv-
applicability depending on the robot type. ery efficiently.
In a recent study [21], a new algorithm for multi-robot A groundbreaking approach was introduced to transform
path planning in hospital environments is introduced by X. the creation of dexterous robotic tools, especially for concen-
Huang, Q. Cao, and X. Zhu. This method combines corridor tric tube robots, as explained in [25]. This innovative method
and room navigation strategies using graph-based approaches combines image-based path planning, robot design, and 3-D
for corridors and artificial potential fields for flexible move- printing technology. It uses preoperative ultrasound images to
ment in rooms. Simulations show that this algorithm signifi- plan safe paths and set critical parameters for the robot. The
cantly improves robot speed in corridors and enables flexible goal is to improve access to diseased areas, especially in pedi-
navigation within rooms. This innovation holds promise for atric patients, during minimally invasive medical procedures.
enhancing multi-robot coordination in complex healthcare This new technique shows great promise for advancing health-
settings. However, there are concerns about its accuracy in care procedures. However, it has limitations like needing
modeling environments and performance in dynamic condi- accurate pre-surgery imaging, potential challenges in cus-
tions, requiring further testing. tomizing robots for each patient, and the need for validation
studies in real clinical settings.
A different paper [22] introduces a new path-planning
method designed for smart wheelchairs. This method uses The SERROGA research project focuses on creating a
the adaptive polymorphic ant colony algorithm and includes robot companion for older individuals to help with their health
strategies to handle challenges and find better paths. Com- needs at home [26]. This paper presents the robot’s architec-
pared to other ant colony algorithms, it performs exceptionally ture, abilities, and important services as a health assistant. It
well, providing efficient and optimal solutions for healthcare also introduces a new way to measure and evaluate how well
and smart wheelchair navigation. The method is good at the robot navigates in apartments. The research includes tests
finding the best overall paths without being stuck in local in 12 apartments with project staff and seniors, as well as case
problems. Nevertheless, there are also some downsides to