Muhammad Alif Putra Yasa

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About

Muhammad Alif Putra Yasa is a robotics researcher whose work focuses on developing intelligent systems for extreme-environment operations, particularly in search and rescue. His most-cited paper, "Exploration Robot Based On YOLOv8 Algorithm" (2024), addresses a critical gap in disaster response: the need for autonomous robots that can navigate hazardous, human-inaccessible areas after events like earthquakes. By integrating the YOLOv8 object detection algorithm into an exploration robot, Yasa enables real-time identification of survivors, obstacles, and structural hazards, significantly improving the speed and safety of rescue missions. Though early in his career, with 2 citations to date, this work represents a practical fusion of computer vision and robotics for life-saving applications. His contribution lies in bridging advanced AI with rugged hardware, making autonomous exploration more reliable under extreme conditions. Yasa’s research holds promise for reducing human risk in disaster zones and enhancing the effectiveness of first responders. As the field of disaster robotics grows, his work stands as a foundational step toward fully autonomous, vision-guided rescue platforms.