Shamus McNamara
Papers
1
Total Citations
79
H-Index
1
About
Shamus McNamara is a leading researcher in autonomous systems, with a primary focus on machine vision for unmanned aerial vehicle (UAV) navigation and collision avoidance. His most-cited work, "Vision-based detection and tracking of aerial targets for UAV collision avoidance" (2010, 79 citations), addresses a critical challenge in aviation safety: enabling small, lightweight UAVs to detect and avoid mid-air collisions without relying on heavy, power-intensive radar. By pioneering low-cost, vision-based sensing solutions, McNamara has advanced the practical deployment of autonomous drones in shared airspace. His contributions are foundational to the field of sense-and-avoid technology, directly impacting the development of safer, more capable UAVs for applications ranging from package delivery to environmental monitoring. With a career dedicated to bridging computer vision and robotics, McNamara’s work continues to influence how researchers and engineers approach autonomous navigation in complex, dynamic environments.
Research Focus
Key Achievements
Top Papers
- 1