Djelloul Yahiaoui
Papers
1
Total Citations
6
H-Index
1
About
Djelloul Yahiaoui is a researcher whose work centers on advancing autonomous navigation and path planning for mobile robots, with a particular focus on ensuring optimal, collision-free movement in complex indoor environments. His most notable contribution is the development of the RRT-A*-BT hybrid approach, which synergistically combines Rapidly-exploring Random Trees (RRT), the A-Star (A*) algorithm, and Back-Tracking (BT) techniques. This innovative framework addresses a critical challenge in robotics: efficiently finding the shortest, safest path through cluttered spaces while avoiding obstacles. The 2019 paper detailing this method has garnered 6 citations, reflecting its practical relevance and impact on the field. Yahiaoui’s work is especially valuable for applications in service robotics, warehouse automation, and assistive technologies, where reliable navigation is paramount. By integrating the exploratory power of RRT with the optimality of A* and the corrective capability of back-tracking, he has provided a robust solution that balances computational efficiency with path quality. His research continues to influence the development of smarter, more adaptable robotic systems, making him a notable contributor to the ongoing evolution of autonomous navigation.
Research Focus
Key Achievements
Top Papers
- 1