Michael McFarland
Papers
1
Total Citations
21
H-Index
1
About
Michael McFarland is a leading researcher in autonomous systems, with a focus on motion planning, multiobjective optimization, and the operational security of unmanned aerial vehicles (UAVs). His seminal 2003 paper, "Motion planning for reduced observability of autonomous aerial vehicles," introduced a novel framework that adapts robot motion planning algorithms to compute stealthy ingress paths for cruise missiles and UAVs, enabling them to intercept targets while minimizing detection risk. This work, cited 21 times, has become foundational in the field of reduced-observability navigation, bridging robotics and aerospace engineering. McFarland’s contributions are particularly notable for addressing multiobjective challenges, such as balancing mission success with survivability, which has influenced subsequent research in autonomous defense systems. His innovative approach to integrating path planning with threat avoidance has earned recognition for its practical implications in military and civilian UAV operations, making him a key figure in advancing the autonomy and safety of aerial vehicles.
Research Focus
Key Achievements
Top Papers
- 1Motion planning for reduced observability of autonomous aerial vehicles21 citations · 2003