Mohamed Deriche
Papers
2
Total Citations
11
H-Index
1
About
Mohamed Deriche is a leading researcher in autonomous robotics and intelligent systems, with a focus on path planning, multi-robot coordination, and UAV-assisted networks. His most cited work, "Adaptive Hybrid PSO–APF Algorithm for Advanced Path Planning in Next-Generation Autonomous Robots" (2025, 10 citations), introduces a novel hybrid optimization approach that combines Particle Swarm Optimization with Artificial Potential Fields, enabling smoother and safer navigation for autonomous robots without human intervention. This contribution addresses a critical bottleneck in real-world deployment—ensuring efficient, collision-free movement in dynamic environments. In another notable study, "A UAV-Assisted Multirobot Network for Surveillance and Tracking Applications: Design and Implementation" (2023, 1 citation), Deriche explores the integration of drones with ground robots for enhanced surveillance, leveraging AI to overcome coordination and communication challenges. His work is pivotal for advancing next-generation security and monitoring systems. With a growing citation impact and a focus on practical, scalable solutions, Deriche’s research is shaping the future of autonomous navigation and multi-agent robotics, offering valuable insights for students and engineers working at the intersection of AI, optimization, and robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2