Ahmad Ali AlZubi

King Saud University

Papers

2

Total Citations

38

H-Index

2

About

Ahmad Ali AlZubi is a leading researcher in autonomous robotics, with a primary focus on perception, navigation, and multi-robot collaboration. His work addresses critical challenges in enabling robots to operate safely and efficiently in complex, dynamic environments. AlZubi’s most influential contribution is his work on obstacle detection and tracking using RGB-D sensor data, which provides a robust solution for real-time environmental awareness in cluttered settings—a paper that has garnered 24 citations. He is also the architect of CORB2I-SLAM, an adaptive collaborative visual-inertial SLAM framework that allows multiple robots to generate a unified global map of unknown spaces using heterogeneous sensors. This innovation, cited 14 times, is pivotal for scalable multi-robot systems in search-and-rescue and industrial automation. By integrating visual and inertial data, AlZubi’s research enhances the reliability of autonomous navigation under challenging conditions. His work not only advances the theoretical foundations of robotic perception but also offers practical, deployable solutions for real-world applications, making him a notable figure in the field of intelligent robotics.

Research Focus

Key Achievements

2
H-Index
2
Papers
38
Total Citations
19
Avg Citations/Paper
🏆 Most Cited Paper
Efficient Obstacle Detection and Tracking Using RGB-D Sensor Data in Dynamic Environments for Robotic Applications
24 citations · 2022
📈 Most Prolific Year: 2022 (2 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: King Saud University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago