Papers
16
Total Citations
701
H-Index
11
About
Carlo Masone is a versatile robotics researcher whose work spans visual place recognition, aerial robotics, cable-driven systems, and human-robot interaction. Based at institutions including the Max Planck Institute for Biological Cybernetics, Masone has made substantial contributions to how robots perceive, navigate, and cooperate in complex environments. His highly cited survey on deep visual place recognition (2021, 184 citations) has become an essential reference for researchers across computer vision, robotics, and machine learning, synthesizing advances in how autonomous systems recognize locations from imagery. Complementing this, his 2022 work on sequential descriptors further pushed the boundaries of sequence-based localization for mobile robots. Masone has also distinguished himself in aerial robotics, notably through foundational research on UAV bearing formations (111 citations) and cooperative quadrotor payload transportation (80 citations), establishing elegant frameworks for multi-robot coordination. His involvement in developing the CableRobot Simulator at the Max Planck Institute — a groundbreaking large-scale motion platform — reflects his engineering ingenuity (112 citations). Additionally, his work on shared human-robot control and bilateral haptic feedback demonstrates a commitment to intuitive human-robot collaboration. With over 650 cumulative citations across diverse topics, Masone represents a rare blend of theoretical rigor and applied innovation in modern robotics research.
Research Focus
Key Achievements
Top Papers
- 1A Survey on Deep Visual Place Recognition184 citations · 2021
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- 5Learning Sequential Descriptors for Sequence-Based Visual Place Recognition42 citations · 2022
- 6Shared planning and control for mobile robots with integral haptic feedback34 citations · 2018
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