Amal Kacem

University of Michigan–Dearborn

Papers

1

Total Citations

4

H-Index

1

About

Amal Kacem is a researcher specializing in industrial robotics, with a particular focus on optimizing robotic systems for manufacturing applications like collaborative car painting. Her work addresses the critical challenge of determining optimal fixed base placements for multiple articulated robotic arms on factory floors or ceilings, ensuring maximum paint coverage while minimizing operational constraints. This contribution is vital for advancing automation in the automotive industry, where precision and efficiency are paramount. Her most-cited paper, "Automatic Optimal Robotic Base Placement for Collaborative Industrial Robotic Car Painting" (2024), has already garnered 4 citations, reflecting its early impact in the field. Kacem's research bridges robotics, optimization algorithms, and industrial engineering, offering practical solutions to complex spatial planning problems. Her work is particularly notable for its focus on collaborative robotics, where multiple arms must coordinate seamlessly. By tackling the base placement problem, she is helping to reduce setup costs and enhance production flexibility, making her a promising voice in the next generation of manufacturing innovation.

Research Focus

Key Achievements

1
H-Index
1
Papers
4
Total Citations
4
Avg Citations/Paper
🏆 Most Cited Paper
Automatic Optimal Robotic Base Placement for Collaborative Industrial Robotic Car Painting
4 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: University of Michigan–Dearborn

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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