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About

Daniel Ruiz is a researcher whose work spans mobile robotics, indoor positioning systems, and robotic-assisted surgery. His most significant contributions lie in the development and refinement of Ultrasonic Local Positioning Systems (ULPS) for mobile robot navigation, an area where he has produced a cohesive and progressive body of research. His most cited work, "Extensive Ultrasonic Local Positioning System for navigating with mobile robots" (2013, 31 citations), demonstrated how fusing ultrasonic beacon measurements with onboard odometry dramatically improves robot positioning accuracy across large environments. Building on this foundation, Ruiz tackled the practical challenge of system deployment through innovative self-calibration methods, enabling LPS networks to configure themselves autonomously — a contribution that significantly reduces setup complexity in real-world applications. His 2014 work extended coverage by integrating isolated beacons into regions lacking full LPS infrastructure, showcasing his commitment to scalable, practical solutions. Beyond robotics navigation, Ruiz has also explored the intersection of robotics and medicine, investigating force and torque analysis in minimally invasive robotic surgery, addressing the critical absence of haptic feedback in commercial surgical systems. Together, his publications reflect a researcher dedicated to bridging precise localization technology with meaningful real-world applications.