F. Leo Princely
Papers
3
Total Citations
40
H-Index
2
About
F. Leo Princely is a researcher whose work sits at the intersection of robotics, manufacturing, and computer vision, with a primary focus on automating the finishing of industrial cast parts. His key contribution is pioneering a "teach-less" robotic system for deburring—the removal of sharp edges and burrs from metal workpieces. This work directly addresses a critical bottleneck in batch production: the time-consuming and labor-intensive process of manually programming robots for each new part shape. His most cited paper, "Vision Assisted Robotic Deburring of Edge Burrs in Cast Parts" (2014, 35 citations), introduces a system that uses a camera to automatically identify a workpiece's geometry, eliminating the need for traditional "teach" or offline programming. This innovation dramatically reduces setup time and increases flexibility for manufacturers. Princely further refined this approach by applying the TOPSIS multi-criteria decision-making method to optimize deburring process parameters, as detailed in his 2019 paper. His work represents a significant step toward more autonomous and adaptable industrial robots, making high-mix, low-volume manufacturing more efficient and accessible.
Research Focus
Key Achievements
Top Papers
- 1Vision Assisted Robotic Deburring of Edge Burrs in Cast Parts35 citations · 2014
- 2
- 3Teach Less Robotic System for Deburring Workpieces of Various Shapes2 citations · 2015