Jesse Batsche
Papers
1
Total Citations
4
H-Index
1
About
Jesse Batsche is a researcher whose work lies at the intersection of robotics, computer vision, and advanced manufacturing. His key research areas include large-shape formation control, uncalibrated vision systems, and precision surface characterization. Batsche’s major contribution is the development of a "virtual mold" approach that leverages laser-spot assisted, 3D image analysis to enable precise and robust control of large-scale deformable shapes without requiring calibrated sensors. His 2008 paper, "Precise and Robust Large-Shape Formation Using Uncalibrated Vision for a Virtual Mold," has garnered 4 citations and stands as a foundational study in this niche. In this work, Batsche demonstrated through surface-reduction-gauging experiments how uncalibrated vision can characterize surface geometry with high precision, revealing critical relationships between measurement accuracy and shape control. His findings have implications for industries requiring adaptive forming processes, such as aerospace or automotive manufacturing. While his citation count is modest, Batsche’s work is notable for its innovative fusion of vision-based feedback and control theory, offering a practical pathway toward more flexible and cost-effective manufacturing systems.
Research Focus
Key Achievements
Top Papers
- 1