Papers
13
Total Citations
336
H-Index
8
About
Mohamed Abdelkader is a robotics and autonomous systems researcher whose work centers on aerial swarm intelligence, multi-robot localization, and UAV coordination. His most influential contribution, "Aerial Swarms: Recent Applications and Challenges" (2021, 159 citations), has become a key reference in the field, reflecting his deep expertise in coordinating autonomous aerial systems at scale. A recurring theme across his research is enabling robots to operate without reliance on external infrastructure: his work on ultrawideband-based peer-to-peer and infrastructure-free localization (2019–2020, accumulating nearly 100 citations combined) offers practical solutions for GPS-denied environments, a persistent challenge in real-world swarm deployment. Abdelkader has also pushed boundaries in trajectory prediction, proposing the VECTOR neural network framework for real-time 3D UAV path forecasting, and in robotic exploration, developing semantic hazard mapping tools for urban search-and-rescue scenarios. His practical engineering contributions span distributed path planning algorithms, adversarial multi-UAV game implementations, and industrial inspection platforms like FalconScan. A recent survey on ROS 2 further demonstrates his commitment to the broader robotics community. With over 320 cumulative citations, Abdelkader's research bridges theoretical rigor with deployable, real-world autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1Aerial Swarms: Recent Applications and Challenges159 citations · 2021
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- 3Infrastructure-free Multi-robot Localization with Ultrawideband Sensors33 citations · 2019
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- 8RISCuer: a reliable multi-UAV search and rescue testbed9 citations · 2021
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