Papers
13
Total Citations
233
H-Index
7
About
Karol Majek is a leading researcher in search-and-rescue robotics, with a core focus on integrating multi-domain robotic systems—including unmanned ground, aerial, and marine vehicles—into coordinated disaster response operations. His most cited work, "Integrated Data Management for a Fleet of Search‐and‐rescue Robots" (103 citations), established foundational frameworks for fusing heterogeneous sensor data from robotic teams into actionable intelligence for human responders. Majek’s contributions extend to parallel computing for robotics, where his research on general-purpose GPU computing (23 citations) dramatically reduced the computational complexity of 3D point cloud processing, enabling real-time environmental mapping in cluttered disaster zones. He is also a key figure in open-source robotics, having developed a widely-used 3D mapping framework based on ROS, PCL, and Cloud Compare (17 citations). Majek’s practical impact is demonstrated through his leadership in the ICARUS team during the euRathlon 2015 challenge, where he validated multi-domain robotic coordination in realistic search-and-rescue scenarios. His recent work on lightweight object detection (2025) continues to push the boundaries of autonomous perception in high-resolution imagery. With over 200 total citations, Majek’s research bridges the gap between theoretical robotics and life-saving field applications.
Research Focus
Key Achievements
Top Papers
- 1Integrated Data Management for a Fleet of Search‐and‐rescue Robots103 citations · 2016
- 2Search and Rescue Robotics - From Theory to Practice34 citations · 2017
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- 9Lesson Learned from Eurathlon 2013 Land Robot Competition4 citations · 2014
- 10A game for robot operation training in search and rescue missions3 citations · 2014