Timothy W. Ubbens
Papers
1
Total Citations
11
H-Index
1
About
Timothy W. Ubbens is a researcher whose work lies at the intersection of robotics, computer vision, and machine learning. His most-cited paper, "Vision-based obstacle detection using a support vector machine" (2009, 11 citations), introduces a monocular vision-based method for mobile robots to detect obstacles in real time. By mounting a single camera on the front of a robot and training a support vector machine (SVM) to classify obstacles as they are encountered, Ubbens addresses a fundamental challenge in autonomous navigation: how to detect hazards without relying on expensive or bulky sensors. This work is notable for its practical approach to a problem that is central to the development of safe, autonomous mobile robots. While his citation count is modest, the paper's focus on efficient, learning-based obstacle detection reflects a forward-thinking application of machine learning to robotics. Ubbens’ contributions are particularly relevant for researchers and students interested in low-cost, vision-based navigation systems, and his work serves as a stepping stone for more advanced perception algorithms in field robotics.
Research Focus
Key Achievements
Top Papers
- 1Vision-based obstacle detection using a support vector machine11 citations · 2009