Papers
6
Total Citations
47
H-Index
5
About
Federico Rollo is an emerging robotics researcher whose work bridges human-robot interaction, teleoperation, and autonomous manipulation systems. His research spans several interconnected domains, including shared-autonomy telemanipulation, semantic mapping, person re-identification, and adaptive robotic assistance — areas that collectively address the challenge of deploying intelligent robots in real-world human environments. Rollo's most impactful contribution, "A Target-Guided Telemanipulation Architecture for Assisted Grasping" (2022, 20 citations), introduced a sophisticated framework for reducing operator workload during prolonged teleoperation tasks, blending human intelligence with robotic precision. Complementing this, his work on Learning from Demonstration and bimanual task learning through Dynamic Movement Primitives demonstrates a commitment to intuitive robot programming paradigms. His research on person following and continuous re-identification tackles the practical complexity of multi-person environments in industrial and domestic settings, moving beyond simplistic single-user assumptions. Rollo has also advanced semantic mapping techniques for 3D object localization and contributed to high-force gripper design with embedded multimodal sensing, reflecting a versatile engineering perspective. With a growing citation record across publications from 2022 to 2024, Federico Rollo represents a promising voice in next-generation collaborative and assistive robotics research.
Research Focus
Key Achievements
Top Papers
- 1A Target-Guided Telemanipulation Architecture for Assisted Grasping20 citations · 2022
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- 4Continuous Adaptation in Person Re-identification for Robotic Assistance5 citations · 2024
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