Mohammad Aldibaja
Papers
1
Total Citations
17
H-Index
1
About
Mohammad Aldibaja is a leading researcher in autonomous vehicle perception and navigation, with a core focus on vision-based motion planning and environmental understanding. His major contributions center on developing robust, real-time trajectory generation methods for autonomous mobile robots, particularly through the innovative use of Bézier curves to ensure smooth obstacle avoidance. In his highly cited 2015 work, Aldibaja introduced a novel approach that generates smooth motion trajectories directly from top-view images captured by fisheye lenses, enabling wide-area environmental perception even at low vehicle heights. This method, which has garnered 17 citations, addresses critical challenges in real-time navigation by accurately detecting and correcting obstacle corners. His work bridges the gap between low-cost sensor configurations and reliable autonomous driving, demonstrating significant impact in the field of mobile robotics. Aldibaja's research continues to influence the development of safer, more efficient autonomous systems, making him a notable figure in advancing practical solutions for self-driving vehicles and intelligent transportation.
Research Focus
Key Achievements
Top Papers
- 1