Chiara Boretti

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About

Chiara Boretti is a robotics researcher whose work bridges neuromorphic vision and bio-inspired navigation for autonomous systems. Her key research areas include event-based vision, person detection for mobile robotics, and visual navigation strategies drawn from biological systems. Her most impactful contribution is the **PEDRo dataset** (2023, 24 citations), a pioneering event-based dataset for person detection in robotics. This work leverages neuromorphic sensors—which offer high-speed, low-latency, and low-power operation—to enable mobile robots to reliably detect and monitor people in dynamic environments. Boretti’s second major contribution, **Visual Navigation Using Sparse Optical Flow and Time-to-Transit** (2022, 7 citations), takes inspiration from the classic behavioral strategy of diving seabirds, showing how a monocular camera can provide robust navigation signals without heavy computation. This biologically grounded approach offers a lightweight, efficient alternative for robot guidance. Boretti’s research is notable for its fusion of hardware-driven sensing with nature-inspired algorithms, advancing practical, real-time robotics applications. Her work is especially relevant for students and researchers interested in neuromorphic computing, autonomous navigation, and the intersection of biology and robotics.