C. Lanzoni

Papers

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About

C. Lanzoni is a researcher in robotics, specializing in motion planning for non-holonomic and car-like mobile robots. Their work bridges deterministic sampling and sensor-based navigation, offering practical solutions for robots operating in complex, unknown environments. Lanzoni’s 2004 paper on low-discrepancy sequences in non-holonomic motion planning (10 citations) introduced a novel approach that replaces random sampling with deterministic sequences, enhancing the efficiency of Probabilistic Roadmap (PRM)-based planners. This contribution addresses a key challenge in robotics: ensuring reliable path computation for vehicles with kinematic constraints. In a companion 2004 study (8 citations), Lanzoni tackled sensor-based motion planning for car-like robots in unknown settings, developing adaptive versions of Lazy DRM and Lazy LRM algorithms. These methods leverage real-time sensor data to compute collision-free paths, enabling robots to navigate dynamically while executing local maneuvers. Though modest in citation counts, Lanzoni’s work is notable for its early integration of deterministic sampling into non-holonomic planning—a precursor to later advances in sampling-based algorithms. Their research remains relevant for students and engineers exploring motion planning under uncertainty, particularly for autonomous vehicles and field robotics.