Papers

1

Total Citations

7

H-Index

1

About

Paul Barsch is a robotics researcher specializing in autonomous navigation and simultaneous localization and mapping (SLAM) for industrial mobile robots. His work focuses on enabling flexible, efficient operation in dynamic factory environments through cooperative long-term SLAM approaches. His most-cited paper, "Cooperative longterm SLAM for navigating mobile robots in industrial applications" (2016, 7 citations), addresses the critical challenge of maintaining precise, up-to-date navigation maps in changing industrial settings. Barsch's key contribution lies in developing methods for multiple robots to collaboratively build and update maps over extended periods, overcoming the limitations of static mapping in environments where layouts frequently shift. This work directly supports reliable localization and dynamic path planning—essential components for autonomous material transport and logistics in manufacturing. While his citation count reflects a focused, applied research niche rather than broad recognition, his contributions are valuable for practitioners implementing robust long-term autonomy in real-world industrial deployments. Barsch's research bridges the gap between theoretical SLAM advances and practical requirements for scalable, persistent robot navigation in production environments.

Research Focus

Key Achievements

1
H-Index
1
Papers
7
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Cooperative longterm SLAM for navigating mobile robots in industrial applications
7 citations · 2016
📈 Most Prolific Year: 2016 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Fraunhofer Institute for Manufacturing Engineering and Automation

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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