Sammie Katt

Northeastern University, University of New Hampshire at Manchester, Universidad del Noreste

Papers

Total Citations

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About

Sammie Katt is a robotics and artificial intelligence researcher whose work centers on autonomous planning, perception, and object manipulation in complex, real-world environments. Their most influential contribution, "Online Planning for Target Object Search in Clutter under Partial Observability" (2019), addresses one of robotics' enduring challenges: enabling robots to locate and grasp target objects in cluttered, uncertain settings where noisy perception and occlusion complicate recognition. This work has garnered 68 citations, establishing Katt as a notable voice in the field of probabilistic planning and human-robot interaction. Complementing this, their 2021 paper on anytime versus real-time heuristic search investigates how AI systems can make effective decisions under strict time constraints — a critical consideration for deployed robotic agents. Katt has also contributed to visual SLAM research, exploring how dynamic objects can be removed to improve static scene reconstruction using light fields. Their early involvement with the UvA Rescue Team at RoboCup 2012 reflects a longstanding commitment to applied robotics in challenging rescue scenarios. Across their career, Katt's research consistently bridges theoretical planning algorithms with practical robotic perception and navigation challenges.