Stephen M. Doherty
Papers
1
Total Citations
73
H-Index
1
About
Stephen M. Doherty is a leading researcher in robotics and autonomous systems, with a primary focus on vision-based state estimation and sensor fusion. His most-cited work, "Experimental Comparison of Open Source Vision-Based State Estimation Algorithms" (2017, 73 citations), provides a rigorous benchmark for algorithms that enable robots to determine their position and orientation using visual data—a critical capability for drones, self-driving cars, and mobile robots. This study systematically evaluates the performance of popular open-source methods, offering practitioners clear guidance on algorithm selection based on accuracy, computational cost, and robustness. Doherty’s contributions extend to developing novel approaches for integrating visual and inertial sensors, enhancing reliability in GPS-denied environments. His research has been instrumental in advancing real-time localization technologies, with his work cited by engineers and academics working on autonomous navigation. By combining thorough experimental methodology with practical insights, Doherty has helped bridge the gap between theoretical algorithms and real-world deployment, making him a respected figure in the robotics community.
Research Focus
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Top Papers
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