Hannah Kolano

Papers

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About

Hannah Kolano is a robotics researcher specializing in precision manipulation for agriculture and underwater environments. Her work centers on developing autonomous control systems that enable robots to perform delicate, force-sensitive tasks—such as pruning fruit trees or operating subsea manipulators—with human-level accuracy. Kolano’s major contribution is a learned hybrid vision/interaction controller that allows a robotic arm to simultaneously align a cutting tool at the correct angle while avoiding excessive force on rigid structures like tree trunks or support posts. This work, published in 2022, has garnered 16 citations and represents a significant step toward fully autonomous precision agriculture. She also leads the development of WAVE (underWater Arm-Vehicle Emulator), an open-source simulation platform for underwater vehicle manipulator systems (UVMS), which has already attracted 9 citations since its 2024 release. By providing a free, accessible tool for testing UVMS autonomy, Kolano is helping to reduce reliance on human support teams for subsea operations. Her research bridges the gap between agricultural robotics and marine manipulation, demonstrating a rare versatility in applying shared control principles across vastly different domains.