Lorenzo Mauro

Papers

Total Citations

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About

Lorenzo Mauro is a researcher at the forefront of human-robot collaboration, specializing in anticipatory robotics and assistive task execution. His work centers on enabling robots to proactively predict human actions and goals, rather than simply reacting to commands—a paradigm shift toward truly intuitive human-robot interaction. Mauro’s key contributions include developing frameworks for next-action prediction and goal anticipation, allowing robots to plan and offer assistance before a need is explicitly stated. His 2019 papers, including "Help by Predicting What to Do" and "Anticipating Next Goal for Robot Plan Prediction," each with 6 citations, lay the groundwork for this anticipatory capability. He also advanced robot task monitoring and visual search, as seen in "Deep Execution Monitor for Robot Assistive Tasks" and "Visual search and recognition for robot task execution and monitoring," which address how robots can visually locate targets and verify task completion in dynamic environments. Though early in his career, Mauro’s focused body of work is establishing a foundation for more autonomous, helpful robotic assistants, promising safer and more efficient collaboration in settings from manufacturing to healthcare.