Razika Boushaki Zamoum
Papers
2
Total Citations
11
H-Index
2
About
Razika Boushaki Zamoum is a researcher at the forefront of intelligent robotics and autonomous systems, with a focus on human-robot collaboration and unmanned aerial vehicle (UAV) navigation. Her work bridges the gap between theoretical machine learning and practical industrial applications. A key contribution is her 2018 study on mission allocation for human and robot agents in industrial environments, where she pioneered the use of RFID sensor platforms to dynamically describe and adapt to environmental states, enabling safer and more efficient cooperative task execution. This foundational work has garnered 7 citations, reflecting its relevance to the growing field of Industry 4.0. More recently, in 2025, she published a comprehensive review on machine learning paradigms for UAV path planning, addressing critical challenges in safety, efficiency, and environmental complexity. This paper, already with 4 citations, highlights her leadership in synthesizing state-of-the-art techniques for autonomous navigation in military and civilian contexts. Boushaki Zamoum’s research is notable for its practical orientation, directly informing the design of resilient, adaptive robotic systems that operate alongside humans in complex, real-world settings.
Research Focus
Key Achievements
Top Papers
- 1
- 2Machine Learning Paradigms for UAV Path Planning: Review and Challenges4 citations · 2025