Amir Ali Nikkhah
Papers
1
Total Citations
9
H-Index
1
About
Amir Ali Nikkhah is a researcher specializing in autonomous aerial robotics, trajectory optimization, and multiobjective decision-making under dynamic constraints. His most cited work, "Nonlinear Multiobjective Time-Dependent TF/TA Trajectory Planning Using a Network Flow–Based Algorithm" (2015, 9 citations), tackles the complex challenge of planning optimal, time-dependent flight paths for unmanned aerial vehicles (UAVs) operating in low-altitude terrain following and threat avoidance missions. By introducing a modified minimum cost network flow algorithm on a grid-based discrete scheme, Nikkhah advanced the practical integration of nonlinear dynamics with real-time path planning—a critical capability for modern autonomous systems. His contributions bridge theoretical optimization and applied robotics, offering scalable solutions for UAV navigation in contested or hazardous environments. While his citation count reflects a focused, emerging impact, Nikkhah’s work is notable for its methodological rigor and direct relevance to defense, surveillance, and disaster response applications. For students and researchers in aerial robotics, his research provides a foundational framework for balancing competing objectives like fuel efficiency, safety, and mission timeliness in autonomous flight.
Research Focus
Key Achievements
Top Papers
- 1