Raffaele Brilli
Papers
3
Total Citations
12
H-Index
2
About
Raffaele Brilli is a researcher advancing the frontiers of autonomous aerial robotics, with a primary focus on enhancing the safety and reliability of Micro Aerial Vehicles (MAVs) during teleoperation. His work centers on two critical challenges: reactive collision avoidance and robust visual navigation in degraded environments. Brilli’s most impactful contribution is the development of a monocular reactive collision avoidance system for MAV teleoperation, leveraging deep reinforcement learning to enable semi-autonomous obstacle avoidance—a capability that compensates for the limited situational awareness of remote human operators. This work, published in 2023, has already garnered 6 citations, reflecting its relevance to the field. He has also investigated visual simultaneous localization and mapping (VSLAM) under low-light conditions, comparing state-of-the-art algorithms like DSO and ORB-SLAM3, and exploring the use of deep learning-based image enhancement to improve performance. His earlier research on force-field-based collision avoidance further underscores his commitment to intuitive, safe drone teleoperation. Through these contributions, Brilli is helping to make aerial robots more accessible and dependable for real-world applications, from inspection to search-and-rescue.
Research Focus
Key Achievements
Top Papers
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