Francisco Mendoza-Galindo

Papers

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About

Francisco Mendoza-Galindo is a researcher specializing in intelligent sensing systems, robotics, and signal processing. His work bridges the gap between advanced sensor technologies and autonomous control algorithms, with a focus on real-time performance and practical implementation. In his most cited work, "An Architecture for Measuring Joint Angles Using a Long Period Fiber Grating-Based Sensor" (2014, 16 citations), Mendoza-Galindo introduced a novel approach to joint angle measurement by employing the Recursive Least Square (RLS) algorithm. This method achieved a critical balance between computational efficiency and system responsiveness, enabling low-lag, resource-conscious filtering for real-time sensor applications. His contributions to robotics are further demonstrated in "Intelligent Algorithm for Parallel Self-Parking Assist of a Mobile Robot" (2012, 4 citations), where he developed a validated strategy for autonomous parallel parking using a tricycle mobile robot. By accounting for robot dimensions and minimal distance requirements, his algorithm provided a robust framework for self-parking maneuvers. Mendoza-Galindo’s work exemplifies the integration of intelligent algorithms with physical sensing, offering practical solutions for automation and assistive technologies. His research continues to influence the development of efficient, real-time control systems in robotics and sensor networks.