Angelos Plastropoulos
Cranfield University, London South Bank University, Innovative Technology and Science (United Kingdom)
Papers
9
Total Citations
55
H-Index
4
About
Angelos Plastropoulos is a robotics and autonomous systems researcher whose work sits at the intersection of mobile robot navigation, machine learning, and industrial inspection applications. His primary focus centers on advancing intelligent navigation systems for complex, dynamic environments — particularly within aviation Maintenance, Repair, and Overhaul (MRO) hangar settings, where precision and safety are paramount. Plastropoulos has made notable contributions through the development of hybrid navigation frameworks, including an improved RRT-DWA obstacle detection and avoidance model and the NAV-YOLO system, which together have accumulated over 27 citations since their 2024 publication — a remarkable early-career impact. His CNN-fusion architecture combining visual and thermographic imaging for object detection further demonstrates his innovative approach to perception in autonomous systems. Beyond aerial infrastructure, his research extends to specialized climbing robots for non-destructive testing (NDT), including mooring chain inspection and reinforced concrete structure assessment, reflecting a broad commitment to robotics-aided safety inspection. His 2025 comprehensive review of robotics in aircraft non-destructive inspection signals his growing role as a synthesizer of knowledge in the emerging "smart hangar" domain. Plastropoulos represents a new generation of researchers bridging sustainable aviation ambitions with cutting-edge autonomous robotics solutions.
Research Focus
Key Achievements
Top Papers
- 1
- 2Mobile Robot Obstacle Detection and Avoidance with NAV-YOLO9 citations · 2024
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- 4The ‘hangar of the future’ for sustainable aviation5 citations · 2024
- 5
- 6Mooring chain climbing robot for NDT inspection applications4 citations · 2018
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