Susanne Martin

Institute of Automation

Papers

1

Total Citations

9

H-Index

1

About

Susanne Martin is a leading researcher in robotic automation, with a primary focus on advancing industrial bin picking systems—a critical challenge in handling unsorted parts. Her most-cited work, "Virtual training and commissioning of industrial bin picking systems using synthetic sensor data and simulation" (2021, 9 citations), tackles the high costs and complex setup requirements that have long hindered practical automation solutions. Martin’s key contribution lies in developing a virtual commissioning framework that leverages synthetic sensor data and simulation to drastically reduce the time and expense of deploying bin picking systems. By enabling realistic training and testing in a digital environment, her approach bridges the gap between theoretical robotics and real-world manufacturing, making automation more accessible for industries like logistics and assembly. Though her citation count is still growing, this work has already been recognized as a foundational step toward scalable, cost-effective robotic handling. Martin’s research continues to shape how engineers approach unsorted part manipulation, offering a pragmatic path to smarter, more adaptable factories.

Research Focus

Key Achievements

1
H-Index
1
Papers
9
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
Virtual training and commissioning of industrial bin picking systems using synthetic sensor data and simulation
9 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Institute of Automation

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 10 days ago