Papers

4

Total Citations

35

H-Index

3

About

Philipp Scholl is a researcher at the intersection of robotics, wireless sensor networks, and intelligent automation. His work focuses on enabling seamless communication between distributed sensor systems and robotic platforms, with a particular emphasis on inertial motion tracking and adaptive control. Scholl’s most cited paper (14 citations) introduces a learning-based approach to adapt robotic friction models, addressing a critical challenge in human-robot collaborative manufacturing within the Fourth Industrial Revolution. He is also recognized for pioneering the integration of wireless sensor networks with the Robot Operating System (ROS), as demonstrated in his 2013 work (12 citations), which simplifies the interface between vendor-specific embedded systems and ROS middleware. Additionally, Scholl developed the jNode platform (7 citations), a wireless sensor network supporting distributed inertial kinematic monitoring—a key contribution to motion tracking in unstructured environments. His 2014 follow-up on ROS integration further solidifies his role in bridging hardware and software for autonomous systems. With a total of 35 citations across his top works, Scholl’s contributions are foundational for researchers and students working on adaptive robotics, sensor fusion, and Industry 4.0 applications.

Research Focus

Key Achievements

3
H-Index
4
Papers
35
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
Learning-based adaption of robotic friction models
14 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 14
🏛 Institutions: Ludwig-Maximilians-Universität München, Technische Universität Darmstadt

Top Papers

  1. 1
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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago