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About

David Gualda is a researcher specializing in acoustic and ultrasonic indoor positioning systems, mobile robot navigation, and signal processing. His work addresses one of modern technology's persistent challenges: accurately determining the location of people and robots inside buildings, where GPS signals are unreliable or unavailable. Gualda's most influential contribution is his development of Acoustic Local Positioning Systems (ALPS) using encoded emission beacons, which has garnered 75 citations and demonstrated centimeter-level indoor accuracy at relatively low cost. His research portfolio spans the full stack of positioning technology—from FPGA-based hardware architectures and advanced encoding schemes (Zadoff–Chu, Kasami, and Chirp) to sophisticated algorithms including Extended Kalman Filtering and simultaneous calibration and navigation (SCAN) techniques. His work on extensive ultrasonic systems for mobile robots, which fuses odometry with external beacon measurements, has been particularly impactful in robotics navigation communities. Beyond positioning infrastructure, Gualda has contributed to formation control of nonholonomic robots and participated in the competitive IPIN 2016 indoor positioning benchmarking event, lending his work real-world validation. With over 270 cumulative citations across his top ten papers, his research provides both theoretical rigor and practical frameworks that continue to advance the field of indoor localization.