Daniel Albuquerque

Papers

Total Citations

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About

Daniel Albuquerque is a researcher focused on advancing robotic perception and sensing through millimeter-wave (mmWave) radar technology. His primary research areas include autonomous robot localization, interference-based sensing, and indoor security systems. Albuquerque’s major contribution lies in developing innovative methods that repurpose mmWave radar interference—typically considered a nuisance—as a useful signal for position estimation and intrusion detection. His 2019 paper on robot self-positioning using asynchronous mmWave radar interference, which has garnered 7 citations, demonstrates how robots can determine their location by leveraging interference from other radars in the environment, offering a low-cost alternative to traditional localization systems. A related work on indoor intrusion detection, with 3 citations, extends this concept to security applications, showcasing the versatility of his approach. Though early in his career, Albuquerque’s work is notable for its creative problem-solving and potential impact on robotics and smart environments. His research promises to enhance autonomous navigation and safety systems, making him a promising voice in the field of radar-based sensing.