Design and Experimental Evaluation of a Low-Cost Autonomous Medical Rescue Robot for Hazardous and Conflict-Affected Environments

Emergency rescue operations in hazardous, unstable, and conflict-affected environments expose medical teams and first responders to serious risks, including structural collapse, fire, debris, toxic exposure, communication failure, and restricted access to victims. Robotic systems can reduce direct human exposure by performing early reconnaissance, detecting possible human presence, transmitting visual information, and supporting rescue planning. However, many advanced rescue robots are expensive, complex, and difficult to reproduce in low-resource settings. This paper presents the design, implementation, and experimental evaluation of a low-cost autonomous medical rescue robot developed for simulated hazardous-environment rescue support. The proposed prototype integrates an ESP32 microcontroller, HC-SR04 ultrasonic sensor, PIR motion sensor, Neo-6M GPS module, ESP32-CAM video-streaming module, L298N motor driver, differential-drive DC motors, servo-actuated robotic arm, and rechargeable battery power system. A reactive autonomous control algorithm was implemented to enable low-speed autonomous navigation, obstacle avoidance, human-motion detection, GPS coordinate reporting, live visual monitoring, and basic robotic-arm activation. Experimental testing showed that the robot achieved an average obstacle-response time of approximately 50 ms, distance-measurement accuracy of approximately ±2 cm, and collision-avoidance success of 92% under controlled conditions. PIR-based human detection achieved 100% success for moving subjects within 1–3 m and 93% within 3–5 m, but decreased to 41% for stationary subjects. Video streaming was maintained at 15–20 FPS up to approximately 30 m line-of-sight range, while GPS localization achieved approximately ±3 m accuracy in open outdoor environments. The robot operated continuously for approximately 45 minutes. The findings demonstrate the feasibility of integrating multiple rescue-support functions into an affordable embedded robotic platform. Nevertheless, the prototype remains limited by PIR detection weakness, indoor GPS failure, Wi-Fi range, battery endurance, wheeled mobility, and robotic-arm payload. Future versions should integrate thermal imaging, AI-based victim detection, LiDAR or depth sensing, indoor localization, long-range communication, stronger actuation, and ruggedized mobility.