AI-Powered Robotics for Post-Disaster Survivor Detection and Rescue Path Mapping
| dc.contributor.author | Diana Nansubuga | |
| dc.date.accessioned | 2025-06-20T06:40:56Z | |
| dc.date.available | 2025-06-20T06:40:56Z | |
| dc.date.issued | 2025-05-06 | |
| dc.description | Undergraduate research project | |
| dc.description.abstract | Natural and man-made disasters often highlight the weaknesses in traditional emergency response efforts, especially in countries with limited resources like Uganda. Challenges such as slow response times, difficulty reaching affected areas, and a lack of real-time information frequently result in lost lives and misused resources. This study introduces a robotic dog system enhanced by artificial intelligence, designed to improve the effectiveness of search and rescue missions following disasters. The system incorporates real-time human detection using AI, SLAM for creating environmental maps, and the A* algorithm to plan efficient rescue routes. The robot is powered by a Raspberry Pi and managed through a Flask-based web platform. It includes multiple sensors, such as GPS, ultrasonic detectors, a night vision camera, and directional microphones, allowing it to navigate independently, avoid obstacles, and communicate wirelessly with remote rescue teams. Testing the system in a controlled, disaster-like setting confirmed its ability to locate victims, generate accurate maps, and determine safe paths with high reliability. The results suggest that. This low-cost, locally adaptable solution could play a vital role in speeding up rescue efforts and minimising risks to human responders. By addressing key limitations in current practices, the project adds valuable insights to the field of disaster robotics, particularly In settings where advanced tools are not readily available. | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12311/2716 | |
| dc.language.iso | en | |
| dc.publisher | Uganda Christian University | |
| dc.title | AI-Powered Robotics for Post-Disaster Survivor Detection and Rescue Path Mapping | |
| dc.type | Thesis |