Papers

8

Total Citations

69

H-Index

5

About

Christian Dreher’s research lies at the intersection of robotic manipulation, cognitive architectures, and human-robot interaction, with a strong focus on enabling robots to learn complex tasks from human demonstration. His work is particularly impactful in the domain of remanufacturing and disassembly, where he addresses the challenge of programming robots to handle uncertain product states. Dreher’s most notable contribution is the development of the KIT Gripper, a multi-functional tool designed specifically for disassembly tasks, which has garnered 17 citations and is recognized for its innovative combination of a 5-DoF arm with a dexterous jaw gripper. He also advanced the field with his work on learning temporal task models from bimanual demonstrations, using graph networks to capture object-action relations—a key step toward making robots more autonomous in production environments. His research on the memory system of the ArmarX robot cognitive architecture (19 citations) provides a foundational framework for integrating perception, planning, and execution. Dreher’s achievements include leading the euROBIN first-year robotics hackathon on door-to-door parcel delivery with heterogeneous robot teams, demonstrating his ability to tackle real-world logistics challenges. With over 60 total citations, his work is steadily shaping the future of agile, learning-driven robotic systems.

Research Focus

Key Achievements

5
H-Index
8
Papers
69
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
A memory system of a robot cognitive architecture and its implementation in ArmarX
19 citations · 2023
📈 Most Prolific Year: 2022 (3 Papers)
🤝 Key Collaborators: 92
🏛 Institutions: CE Technologies (United Kingdom), Karlsruhe Institute of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago