Martin S. Brunaes

Papers

Total Citations

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About

Martin S. Brunaes is a researcher focused on the intersection of unmanned aerial vehicle (UAV) technology and computer vision, with a particular emphasis on autonomous navigation systems. His most cited work, "UAV path automation using visual waypoints acquired from the ground" (2020), introduces a novel two-phase system that simplifies drone flight automation by leveraging ground-based image recognition. In the first phase, a manual joystick flight captures visual waypoints along a trajectory; these waypoints then enable automated path replication in subsequent flights. This approach reduces the complexity of UAV programming, making autonomous flight more accessible for applications in surveying, agriculture, and logistics. While his citation count remains modest at 3, the work represents a practical contribution to the field of visual-based UAV control, demonstrating how low-cost, ground-level image processing can replace expensive GPS or LiDAR systems. Brunaes’ research bridges the gap between theoretical computer vision models and real-world robotic applications, offering a scalable solution for small-scale drone operations. His work is particularly relevant for students and engineers seeking to implement cost-effective autonomous navigation in resource-constrained environments.