# Autonomous Mobile Robots in Hospital Logistics

Giuseppe Fragapane, Hans-Henrik Hvolby, Fabio Sgarbossa, Jan Ola
Strandhagen

► To cite this version:

Giuseppe Fragapane, Hans-Henrik Hvolby, Fabio Sgarbossa, Jan Ola Strandhagen. Autonomous Mobile Robots in Hospital Logistics. IFIP International Conference on Advances in Production Management Systems (APMS), Aug 2020, Novi Sad, Serbia. pp.672-679, 10.1007/978-3-030-57993-7_76. hal-03630873

HAL Id: hal-03630873

https://inria.hal.science/hal-03630873

Submitted on 5 Apr 2022

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
Autonomous mobile robots in hospital logistics

Giuseppe Fragapane¹ [0000-0001-8915-509X], Hans-Henrik Hvolby¹,² [0000-0002-5574-5216], Fabio Sgarbossa¹ [0000-0002-9541-3515] and Jan Ola Strandhagen¹ [0000-0003-3741-9000]

¹ Department of Mechanical and Industrial Engineering,

Norwegian University of Science and Technology, Trondheim, Norway

² Centre for Logistics, Department of Materials and Manufacturing Engineering,

Aalborg University, Denmark

giuseppe.fragapane@ntnu.no

**Abstract.** The recent advances in technology have increased flexibility in in-door mobility and human-robot collaboration, opening up new opportunities to perform material handling tasks, especially in narrow, dynamic environments, such as hospitals. Sensing devices, powerful on-board computers, artificial intelligence, and collaborative equipment allow autonomous mobile robots (AMRs) to drive and fulfill material handling activities autonomously. In hospitals, material handling activities are widely performed manually. This study investigates five innovative applications of AMRs, highlighting their benefits compared with other material handling systems applied in hospitals, and presenting research needs. The study concludes that AMRs can support and collaborate closely with hospital personnel to increase value-added time for patient care.

**Keywords:** Autonomous Mobile Robots, Material Handling, Hospital, Logistics

# 1 Introduction

Automating material handling activities can significantly improve efficiency and productivity in the healthcare sector, since hospitals, compared to other industries, still, often perform these activities manually. A large survey conducted in the US, Canada, and Germany exposed that nursing's none-value-adding and non-nursing activities (e.g., delivery and retrieval of food trays, ancillary, or housekeeping services) consume around 40% of nurses' time [1]. Many of these activities could have been accomplished by other hospital personnel or advanced material handling systems [2-4]. However, finding the appropriate material handling system and level of automation for addressing hospitals' and patients' requirements is quite challenging [5]. The common material handling systems applied in hospitals allow low flexibility in mobility. Automated guided vehicles (AGV) cannot bypass obstacles and enter wards or departments due to safety and space concerns. Automated vacuum collection sys-
tems, pneumatic tube systems, and overhead transportation systems often have only
fixed pick and/or delivery stations in departments. The low flexibility in mobility
makes it difficult to automate material handling in the so-called last 50 meters, refer-
ring to the distance in the department to the patient, as well as in other departments.

The need for more flexibility has pushed the development of autonomous mobile
robots (AMRs). Thanks to ubiquitous sensors, powerful on-board computers, artificial
intelligence (AI), and simultaneous location and mapping (SLAM) technology, AMRs
can understand their operating environments and navigate in facilities without the
need to define and implement reference points in advance. AMRs are often small and
agile, and they show their strength in high-traffic environments and low-volume
transportation. Due to AMRs’ characteristics, they can access narrower areas, interact
with healthcare personnel and patients, and provide more services, such as assistive
activities. AMRs have shown great potential in automotive, warehousing and process
industry, in which they have supported increased production flexibility and productiv-
ity [6]. The potential of AMRs’ high accessibility and flexibility in providing services
has not been exploited and investigated in hospital environments.

Therefore, the aim of this paper is (I) to describe innovative material handling ser-
vices and applications of AMRs in hospitals, (II) to compare them with other material
handling systems in hospitals, and (III) to highlight future research needs for AMRs
in hospital logistics. Two case studies have been conducted and three examples from
the literature are presented to achieve these objectives.

The rest of the paper is organized as follows. The next section provides back-
ground information on traditional material handling systems in hospitals. Section
three introduces and explains the cases and examples in which AMR has been applied
in hospitals. The fourth section compares AMRs with other material handling systems
in hospitals. The study ends with recommendations for future research areas for hos-
pital logistics and AMRs.

2 Theoretical background

## 2.1 Material handling systems in hospitals

Logistics and material handling are crucial parts of the healthcare industry. De-
pending on the characteristics of the goods and the delivery requirements, a material
handling system can be assigned to these tasks. Small objects, e.g., samples being
delivered to laboratories, are mainly sent via pneumatic tube systems in hospitals due
to time constraints. While automated vacuum collection systems are only used for
return transportation of waste or linen, overhead transportation systems are used for
both incoming and return transportation of loads of up to 15 kg to different depart-
ments. For transportation of heavier and bigger goods, AGVs have demonstrated good
results in distributing high-volume goods to many pick-and-place positions and trav-
eling long distances within hospitals without disturbing the hospital traffic [7]. The
current material handling systems in hospitals are still largely dependent on human
interaction for preparing, loading/unloading, and sending the items.
In contrast, AMRs have been recently introduced to hospitals, and their applicability in hospital logistics has not been exploited. AMRs possess a wide array of small and power-efficient sensing technologies, such as integrated laser scanners, 3D cameras, accelerometers, gyroscopes, etc., which allow them to digitalize an environment. Processing the sensing data with simultaneous location and mapping technology enables an AMR to create a map of its environment and calculate its position [8]. Unlike AGV systems, in which the central unit makes all routing and thus navigation decisions for all AGVs, AMRs can plan collision-free paths, make real-time decisions to avoid collisions, and so navigate in dynamic and unpredictable environments. AI techniques such as vision systems and machine learning enable the identification and classification of obstacles. These learning techniques enable AMRs to solve complex control problems in unfamiliar, real-world environments.

The main characteristics of the aforementioned material handling systems are shown in Table 1. A recent literature review in material logistics pointed out that standards and best practices for how to transport goods in hospitals barely exist [9]. To the best of the authors' knowledge, the applicability and research needs of AMRs in hospital logistics have not been addressed.

<table><caption>Table 1. Characteristics of automated material handling systems in hospitals</caption><thead><tr><th></th><th>Automated guided vehicle</th><th>Autonomous mobile robot</th><th>Automated vacuum collection system</th><th>Overhead transportation system</th><th>Pneumatic tube system</th></tr></thead><tbody><tr><td>Capacity load</td><td>1–500kg</td><td>1–100kg</td><td>1–50kg</td><td>1–15kg</td><td>up to 2kg</td></tr><tr><td>Transportation speed</td><td>1–2 km/h</td><td>3–4km/h</td><td>20–70km/h</td><td>2–3km/h</td><td>10–25km/h</td></tr><tr><td>Services provided</td><td>Transportation</td><td>Transportation, collaboration, assistance, etc.</td><td>Only return transportation</td><td>Transportation</td><td>Transportation</td></tr><tr><td>Service points</td><td>Fixed pick and delivery points</td><td>Flexible pick and delivery points</td><td>Fixed pick and delivery points</td><td>Fixed pick and delivery points</td><td>Fixed pick and delivery points</td></tr><tr><td>Navigation</td><td>Fixed guided path</td><td>Autonomous in predefined zones</td><td>Fixed tube path</td><td>Fixed guided path</td><td>Fixed tube path</td></tr></tbody></table>

# 3 Cases and examples

## 3.1 Case 1: Sterile instrument transportation

Sterile instruments are transported in wagons from and to departments in a closed-loop logistics system by an AMR. The sterile processing department is responsible for picking and sending the sterile instruments required for medical treatment from the storage area to the departments. After usage at the department level (e.g., operating room), the goods are sent back to the central sterile processing department for cleaning, inspection, and sterilization. Hospital personnel can request, send, and track
transportation via a tablet. Due to the logistics setup and the reliable transportation offered by the AMR, sterile goods can be sent Just-in-Time and demand-based on demand.

There are 10 pick and delivery stations located among five different levels in the case hospital. The AMR can open doors, use elevators, enter departments, bypass obstacles, handle dynamic environments, and reach the destination pickup-and-delivery station to deliver the sterile instruments. The AMR delivers approximately 60 wagons daily and substitutes one full-time employee.

<figure><img src="image_2.png" /><figcaption>Fig. 1. AMR in sterile instrument logistics [10]</figcaption></figure>

## 3.2 Case 2: Personalized cancer medicine transportation

In chemotherapy treatments, patients receive personalized cancer medicine that has a short lifetime and can cost several thousand euros. The medicine is produced in the pharmaceutical department in the basement of the case hospital, while the actual treatment takes place several floors above it. Therefore, high-precision delivery, reliability, safety, and security are required for the transportation of medicine between the two departments.

The case hospital uses an AMR to transport the medicine in a locked drawer from the basement through the hospital to the final destination in the department [10]. After delivery, the AMR returns to the pharmaceutical department and waits to receive the next order. The AMR reduces the healthcare personnel's responsibility and the amount of time involved in the transportation of medicine. This helps healthcare personnel increase patient care and value-added time and thus has enabled the return of the initial investment within one year.

<figure><img src="image_3.png" /><figcaption>Fig. 2. Sending and delivery of cancer medicine with secured transportation [10]</figcaption></figure>
### 3.3 Example 1: AMR providing telemedicine

AMRs with teleoperating and medical equipment can be controlled by a human from a long distance and perform tasks in dynamic environments [11]. Tele-operation enables a new method of using this valuable resource and eases the high risk of infectious disease transfer. Physicians and specialists can communicate with patients and perform some of their duties at a safe distance from infected patients. A telemedicine robot with autonomous navigation technology has been introduced in hospitals in the US [12]. While the AMR moves from room to room, the physician can easily connect for patient consults and access clinical documentation, patient data, and medical imaging. Digitizing and robotizing the material handling activities will provide data for and insights into new options for process improvement.

<figure><img src="image_4.png" /><figcaption>Fig. 3. AMR providing telemedicine [12]</figcaption></figure>

### 3.4 Example 2: Assistive, collaborative AMR in the hospital laboratory

AMRs with manipulators can assist workers by interacting with humans as robotic coworkers. In other industries, AMRs are used as assistive systems and can mount several heavy parts of a car body together at different stages along the car assembly line [13], thus increasing both productivity and quality while simultaneously reducing fatigue levels among workers. A dual-arm mobile robot has been introduced to a US hospital laboratory [14]. The AMR was designed to work alongside medical staff and help complete lab workers’ repetitive tasks (Fig. 4).

<figure><img src="image_5.png" /><figcaption>Fig. 4. Assistive, collaborative AMR in a hospital laboratory [14]</figcaption></figure>
It can sense and navigate its way around its human coworkers autonomously and simultaneously learn to find optimized routes from one location to another. The vision for using AMRs in laboratories is that they will take over a wide range of repetitive and time-consuming activities, such as preparation of medicines, loading and unload- ing centrifuges, pipetting and handling liquids, and picking up and sorting test tubes.

## 3.5 Example 3: AMR disinfecting rooms

Hospitals must clean and disinfect rooms after usage to reduce the spread of haz- ardous bacteria. Hospitals are strategizing to reduce the risk of such spread and simul- taneously increase awareness [15]. The development of UV-C light systems signifi- cantly supports the destruction of bacteria. UV-C light systems need 10 min of expo- sure time to kill 99.99% of bacteria [16]. While the equipment can often be found on wheels and is moved manually from room to room, AMRs provide a platform for autonomously transporting the equipment into and within rooms (Fig. 5a). Therefore, an AMR can cover more surfaces compared to a fixed UV-C system and reduce the exposure of hospital personnel to bacteria (Fig. 5b). Further, it can collect relevant data during the disinfection process and communicate when the room is ready for usage.

<figure><img src="image_6.png" /><figcaption>**Fig. 5a:** AMR with disinfection equipment[16]. **Fig. 5b:** Left room disinfected with stationary equipment; right room disinfected by AMR (green/blue areas symbolizes disinfection range)</figcaption></figure>

# 4 Discussion and conclusion

Unlike other material handling systems applied in hospitals, AMRs utilize AI for decision making, which significantly increases their flexibility in performing material handling activities in hospitals. AI especially supports AMRs’ decision making in path and motion planning. While typically, an A* algorithm is applied in path plan- ning to find the shortest path, AI allows analysis of the dynamic environment and reacts appropriately to congestions. Machine learning techniques can suggest opti- mized paths based on previous deliveries. These processes increase the reliability of precision delivery, which is crucial in hospitals since small delivery deviations can
have large impacts on patient treatment. For instance, missing instruments or medi-
cine will postpone treatments or negatively impact the health of the patient. Robust
and reliable material handling systems like AMRs are crucial for transferring material
flows that can highly impact patient health from manual to automated.

AI can further support interaction between humans and machines, enabling assistive or collaborative tasks. Vision-based sensing, manipulators for grabbing and handling probes, and the use of machine learning allow AMRs to learn to perform a wide variety of repetitive activities. AMRs can function as robotic coworkers in laboratories, autonomously improving both specific processes and overall performance. This allows for the reduction of workload for highly trained laboratory workers.

AMRs can deliver to the point-of-use, the patient, and so cover a wide service area. For many years, mobile robots were a virtually unimaginable and practically unacceptable solution in healthcare support. People could not associate hospitals with a production environment. The increased social acceptance of AMRs allows integration into departments and wards. AMRs can deliver to the point of use, the patient, and so cover a wide service area. The integration of AMRs as transporting, collaborating, or assisting robots allows a rethinking of logistics and material handling activities in hospitals. Therefore, future research should focus on:

* What manual material handling activities should AMRs assist with or take over, and when?

* How should AMRs interact with hospital personnel and patients to achieve high social acceptance and safety?

* How should hospital goods be transported by AMRs to achieve high reliability, productivity, safety, and quality?

* How should AMRs be integrated with AGVs and other stationary automated material handling systems?

* How should AMRs be designed and planned at the strategic level in hospitals?

* How can the optimal number of AMRs be determined in hospital logistics?

* How should path planning and motion planning be adapted for hospital environments?

5 Acknowledgment

This research received funding from the strategic research area of NTNU Health in
2020 at NTNU. The authors would also like to express their gratitude to the Regional
Development Fund in Denmark for supporting the project "Reference architecture and
open standards". Finally, the authors gratefully acknowledge the case hospitals that
made it possible to carry out this study.
References

1. Yen, P. Y., Kellye, M., Lopetegui, M., Saha, A., Loversidge, J., Chipps, E. M., ... & Buck, J. (2018). Nurses' Time Allocation and Multitasking of Nursing Activities: A Time Motion Study. In *AMIA Annual Symposium Proceedings* (Vol. 2018, p. 1137). American Medical Informatics Association.

2. Aiken, L. H., Clarke, S. P., Sloane, D. M., Sochalski, J. A., Busse, R., Clarke, H., ... & Shamian, J. (2001). Nurses' reports on hospital care in five countries. *Health affairs*, 20(3), 43-53.

3. Kudo, Y., Yoshimura, E., Shahzad, M. T., Shibuya, A., & Aizawa, Y. (2012). Japanese pro-fessional nurses spend unnecessarily long time doing nursing assistants' tasks. *The Tohoku journal of experimental medicine*, 228(1), 59-67.

4. Wong, D., Bonnici, T., Knight, J., Gerry, S., Turton, J., & Watkinson, P. (2017). A ward-based time study of paper and electronic documentation for recording vital sign observations. *Journal of the American Medical Informatics Association*, 24(4), 717-721.

5. Granlund, A., & Wiktorsson, M. (2014). Automation in internal logistics: strategic and operational challenges. *International Journal of Logistics Systems and Management*, 18(4), 538-558.

6. Fragapane, G., Ivanov, D., Peron, M., Sgarbossa, F., & Strandhagen, J. O. (2020). Increasing flexibility and productivity in Industry 4.0 production networks with autonomous mobile robots and smart intralogistics. *Annals of Operations Research*, 1-19.

7. Fragapane, G. I., Bertnum, A. B., Hvolby, H. H., & Strandhagen, J. O. (2018). Material distribution and transportation in a norwegian hospital: a case study. *Ifac-papersonline*, 51(11), 352-357.

8. Bloss, R., (2008). Simultaneous sensing of location and mapping for autonomous robots. *Sensor Review*, 28(2): p. 102-107.

9. Volland, J., Fügener, A., Schoenfelder, J., & Brunner, J. O. (2017). Material logistics in hospitals: a literature review. *Omega*, 69, 82-101.

10. MIR Homepage, https://www.mobile-industrial-robots.com/en/insights/case-studies/, last accessed 2020/04/04.

11. Papadopoulos, I., Koulouglioti, C., Lazzarino, R., & Ali, S. (2019). A systematic review of enablers and barriers to the implementation of socially assistive humanoid robots in health and social care. *BMJ Open*, 1-13.

12. Intouch Homepage, https://www.businesswire.com/news/home/20130506005495/en/In Touch-Health-iRobot-Announce-Customers-Install-RP-VITATM, last accessed 2020/04/04.

13. Angerer, S., Strassmair, C., Staehr, M., Roettenbacher, M., & Robertson, N. M. (2012). Give me a hand—The potential of mobile assistive robots in automotive logistics and assembly applications. *In 2012 IEEE International Conference on Technologies for Practical Robot Applications (TePRA)* (pp. 111-116). IEEE.

14. Yumi Homepage, https://new.abb.com/news/detail/37301/abb-demonstrates-concept-of-mobile-laboratory-robot-for-hospital-of-the-future, last accessed 2020/04/04.

15. Goldmann, D. A., Weinstein, R. A., Wenzel, R. P., Tablan, O. C., Duma, R. J., Gaynes, R. P., ... & Burke, J. (1996). Strategies to prevent and control the emergence and spread of antimicrobial-resistant microorganisms in hospitals: a challenge to hospital leadership. *Jama*, 275(3), 234-240.

16. UVD Robots Homepage, http://www.uvd-robots.com/, last accessed 2020/04/04.