Paul H. Guentert
Papers
1
Total Citations
212
H-Index
1
About
Paul H. Guentert is a leading researcher in autonomous systems, with a primary focus on unmanned aerial vehicle (UAV) navigation, path planning, and obstacle avoidance. His most influential work, the 2018 comparative study "Overview of Path-Planning and Obstacle Avoidance Algorithms for UAVs," has garnered over 212 citations, establishing itself as a foundational reference in the field. This paper systematically evaluates the critical "Sense and Avoid" capability, a key challenge for enabling safe UAV operations in civilian airspace. Guentert's contributions extend beyond this survey; his research rigorously compares classical and modern algorithms, providing a clear roadmap for developing more efficient and reliable autonomous navigation. By synthesizing complex technical landscapes, his work has directly guided subsequent innovations in UAV autonomy, making him a pivotal figure for students and researchers seeking to understand or advance the state of the art in robotic navigation.
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