Max Robotics — Global Service Robot Directory + US Certification

About

Agnese Chiatti is a robotics and artificial intelligence researcher whose work sits at the intersection of computer vision, mobile robotics, and intelligent systems. Her research focuses on enabling robots to perceive and interact with complex, dynamic environments — a challenge central to real-world deployment of service and agricultural robots. Chiatti's most influential contribution lies in few-shot object recognition, where her 2020 paper (13 citations) tackled the fundamental limitation of conventional recognition methods by developing task-agnostic approaches that allow mobile robots to identify both familiar and novel objects without exhaustive retraining. She has extended this perceptual work to agricultural robotics, exploring grape bunch segmentation under challenging visual domain shifts, addressing the urgent need for robust robotic monitoring in sustainable farming contexts. Beyond perception, Chiatti has contributed to the broader robotics ecosystem through model-driven software engineering, developing an AADL-to-ROS toolchain that streamlines the translation of complex system models into deployable robot software. Her work also bridges smart city infrastructure and service robotics, as demonstrated through her field report on integrating these domains within competitive robotic settings. Her incorporation of commonsense size-based reasoning further reflects a drive to make robot cognition more human-aligned and practically robust.