Papers
4
Total Citations
33
H-Index
3
About
Boussad Abci’s research lies at the intersection of autonomous robotics, fault diagnosis, and robust control, with a focus on ensuring safety and reliability in multi-robot systems. His major contributions center on developing information-theoretic methods—particularly using Kullback-Leibler divergence—to detect and isolate faulty sensors and actuators in real time. In his most cited work (2019, 18 citations), he introduced an informational approach for sensor and actuator fault diagnosis in autonomous mobile robots, enabling early detection of failures without requiring precise system models. He extended this framework to multi-robot systems (2019, 5 citations), proposing observer-based residual generation that leverages information filters to distinguish between sensor drift and actuator degradation. Abci also integrated fault tolerance with sliding mode control, demonstrating robust navigation even under partial actuator loss (2018, 8 citations; 2019, 2 citations). His work has been presented at international venues and contributes to the growing field of fault-tolerant autonomous navigation. With over 30 cumulative citations, Abci’s research is particularly valuable for students and engineers working on dependable multi-robot coordination, sensor fusion, and safety-critical mobile robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4