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All Journal PROtek : Jurnal Ilmiah Teknik Elektro JOIV : International Journal on Informatics Visualization
Reynaldi, Rindang
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy

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Journal : JOIV : International Journal on Informatics Visualization

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A Low-Cost Nursing Robot with Telemedicine using ESP32 and Robot Operating System-based Suharjono, Amin; Apriantoro, Roni; Supriyo, Bambang; Wardihani, Eni Dwi; Yunanto, Bagus; Hidayat, Wahyu; Prasetio, Katon; Reynaldi, Rindang; Fahrul Aji, Achmad
JOIV : International Journal on Informatics Visualization Vol 9, No 2 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.2.2793

Abstract

The COVID-19 pandemic has presented unprecedented challenges to the healthcare sector, particularly frontline healthcare workers. These professionals face high infection risks and physical and mental exhaustion due to intensified workloads and staffing shortages. Robots are seen as a potential solution to this predicament, performing tasks such as delivering supplies and monitoring patients. However, widespread adoption of such robots, particularly in resource-constrained settings, has been hampered by the exorbitant costs associated with their acquisition and maintenance. To address this problem, the authors developed a low-cost nursing robot based on the ESP32 and the Robot Operating System (ROS). This robot facilitates hospital logistics and patient monitoring through telemedicine. The robot is controlled by remote control or Wi-Fi connection through the RViz Graphical User Interface (GUI) and uses odometry and PID control methods to follow specified paths autonomously. Accessible via local area networks and the Internet, the telemedicine system demonstrates robust performance with minimal X and Y axis control errors, zero packet loss, an average Round Trip Delay (RTD) of less than 150 ms, and jitter values of less than 20 ms, in line with TIPHON standards. This innovation provides a cost-effective solution to support healthcare workers during the ongoing health crisis. In future development, incorporating LiDAR, computer vision, and AI-based decision-making into the robot can facilitate obstacle detection and real-time decision-making to enable fully autonomous movement. These advancements will enhance the robot’s adaptability and accuracy in navigation and positioning.
Co-Authors Amin Suharjono Apriantoro, Roni Bambang Supriyo, Bambang Eni Dwi Wardihani, Eni Dwi Fahrul Aji, Achmad Prasetio, Katon Wahyu Hidayat Yunanto, Bagus