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About

Andrei Stancovici is a researcher specializing in collaborative multi-robot systems, with a particular focus on relative localization, inter-robot distance measurement, and cooperative positioning for indoor environments. His work addresses the fundamental challenge of enabling autonomous robots to accurately determine each other’s positions without relying on external infrastructure—a critical capability for applications ranging from surveillance to industrial automation. Stancovici’s most influential contribution is his 2010 paper on indoor inter-robot distance measurement (12 citations), which proposed two distinct methods optimized for speed, accuracy, and energy efficiency under real-world constraints. He further advanced the field by developing a low-cost ultrasonic localization turret hardware module (2014) and a comprehensive relative localization methodology using triangulation and trilateration (2013). His 2016 work on cooperative positioning for indoor surveillance (7 citations) analyzed error propagation in collaborative teams, proposing methods to maintain accuracy as robots move. Collectively, his research has accumulated over 34 citations, establishing foundational techniques for scalable, infrastructure-free robot coordination. Stancovici’s contributions are particularly valuable for students and engineers working on swarm robotics, autonomous navigation, and distributed sensing systems.