Michelle L. Catigum
Papers
1
Total Citations
3
H-Index
1
About
Michelle L. Catigum is a robotics researcher whose work bridges artificial intelligence and practical automation. Her primary research areas include autonomous mobile robotics, computer vision, and neural network applications for real-world object detection and collection. Her most notable contribution is the development of a neural network vision-guided mobile robot designed to autonomously retrieve driving-range golf balls—a project that demonstrates her ability to integrate machine learning with mechanical engineering. This system uses a neural network to recognize range borderlines via red stripes, while a custom rotating blade mechanism collects scattered balls, showcasing a complete pipeline from perception to physical action. Though her most-cited paper has garnered 3 citations, its novelty lies in addressing a niche but practical problem: automating a tedious task in sports facilities. Catigum’s work exemplifies how neural networks can be deployed in resource-constrained, real-time environments, offering a template for similar agricultural or industrial collection systems. Her achievement highlights the potential of combining AI with mechanical design to solve everyday challenges, making her a notable figure in applied robotics.
Research Focus
Key Achievements
Top Papers
- 1