Lorenzo Pichierri

Papers

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About

Lorenzo Pichierri is a rising leader in multi-robot systems, distributed optimization, and swarm robotics. His work focuses on enabling teams of autonomous robots to coordinate intelligently without centralized control, tackling critical challenges in surveillance, patrolling, and target encirclement. Pichierri’s most influential contribution is **CrazyChoir** (2023, 23 citations), a modular Python framework built on ROS 2 that allows researchers to simulate and deploy real-world swarms of Crazyflie quadrotors with unprecedented ease—a key enabler for experimental robotics. He has also advanced distributed online optimization for cooperative surveillance, proposing algorithms that allow defending robot teams to dynamically adapt to intruders using an aggregative game-theoretic framework (2023, 5 citations). Most recently, Pichierri developed a distributed feedback optimization policy for multi-robot target monitoring and patrolling (2024, 2 citations), designing a peer-to-peer control law that minimizes a comprehensive cost index balancing coverage, persistence, and energy efficiency. His work bridges theory and practice, offering scalable, provably convergent solutions for real-world multi-robot coordination. As a researcher at the intersection of control theory, optimization, and robotics, Pichierri is shaping the future of autonomous swarms for security, environmental monitoring, and beyond.