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About

Riccardo Berra is a robotics researcher whose work bridges the critical gap between autonomous perception and human-robot interaction. His primary research areas include active visual search (AVS), online motion planning under partial observability, and accessible social robotics. Berra’s most significant contributions lie in developing planning algorithms for robots to efficiently locate objects in indoor environments. His POMP framework (2020, 9 combined citations) introduced a Partially Observable Monte Carlo Planning (POMCP) approach for known spaces, while the follow-up POMP++ (2021, 11 citations) extended this to unknown environments, enabling robots to learn optimal search policies online using only RGB-D input and current pose. These works directly address the challenge of real-world robotic perception and navigation. Beyond search, Berra co-developed Berrick (2019, 5 citations), a low-cost, open-source anthropomorphic robotic head designed to democratize research in human-robot social interaction. By focusing on face-to-face dynamics with multimodal sensing, Berrick provides an accessible platform for studying social cues. With a growing citation impact, Berra’s work is shaping how robots perceive, plan, and interact—from efficient object search to engaging socially with humans.