Riccardo Poli

University of Birmingham, University of Essex

Papers

Total Citations

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About

Riccardo Poli is a leading figure in robotics and artificial intelligence, with a career spanning foundational work in mobile robot localisation, continual learning, and cutting-edge medical microrobotics. His most influential contribution, the 2001 paper "Robust mobile robot localisation from sparse and noisy proximity readings using Hough transform and probability grids," has garnered 37 citations and introduced a novel method for enabling robots to determine their position using minimal, imperfect sensor data—a critical advance for autonomous navigation in real-world environments. In 1998, Poli pioneered "Continual Robot Learning with Constructive Neural Networks" (11 citations), laying early groundwork for adaptive systems that can incrementally acquire new skills without forgetting previous knowledge, a challenge now central to modern AI. More recently, his 2022 work on an "Online real-time platform for microrobot steering in a multi-bifurcation" (4 citations) pushes the boundaries of medical robotics, demonstrating real-time control of ferrous microparticle swarms via electromagnetic fields for targeted drug delivery. This research addresses the critical bottleneck of transitioning from slow, accurate simulations to practical, real-time deployment, showcasing Poli’s enduring ability to tackle complex, high-impact problems across robotics and intelligent systems.