Hospital Logistics deals with effective and efficient ways to transport items in hospitals. Autonomous Mobile Robot (AMR) is one of the most widely used automated systems to improve the transportation process. In this research, AMRs are used for delivering food and medical supplies to individual patients. Especially in COVID-19 pandemic situation, AMRs are important tools for keeping physical distance between patients and health workers to prevent infection. In this research, the AMR is equipped with Internet of Things (IoT) module which can be connected to the IoT platform on the server side. As a result, the health workers are able to monitor can control the robots effectively via a web application.

Autonomous Mobile Robots (AMRs) plays a vital role in various logistic applications, especially in the health industry. Precise localization is required for automated navigation of the robot throughout the operations. Docking is one of the key processes that the robot moves and physically attaches to the station. Higher precision in position and orientation is required for this process to ensure the secured connection. This article presents an implementation of precise docking maker technique for localization of the robot. The robot is equipped with affordable Lidar sensor while a geometrical marker is on the docking station. The proposed method should help the robot achieve better than ±20 mm error and 0.05rad error in position and orientation.

Logistic management is crucial for effective and efficient transportation of various items in hospitals. During pandemic situations, especially COVID-19, special in-patient cohort ward is established to treat patients who require special treatment due to the quarantine protocol. Autonomous Mobile Robot (AMR) is used for delivering food and medical supplies to individual patients in order to keep the physical distance between patients and health workers. In this research, delivery by using multiple AMRs working in the in-patient ward is simulated. The simulation software is developed in Unity platform to study the operations of AMRs in various scenarios.

No abstract