Philippe Komma

University of Tübingen

Papers

6

Total Citations

124

H-Index

4

About

Philippe Komma is a leading researcher in autonomous mobile robotics, with a primary focus on terrain classification and perception for outdoor robots. His work bridges computer vision and tactile sensing, developing robust methods for robots to understand their environment. Komma’s major contributions include pioneering high-resolution visual terrain classification using SURF features and grid-based local feature analysis, which achieved 47 and 31 citations respectively. He also advanced vibration-based terrain classification through adaptive Bayesian filtering (30 citations), enabling robots to infer ground surfaces from vibration signals for safer traversal. Notably, Komma developed a real-time number sign detection system for the 2010 “SICK robot day” challenge, demonstrating practical deployment on computationally limited robots. His research extends to Markov random field-based clustering of vibration data, laying groundwork for environmental structure mapping. With over 120 total citations, Komma’s work has significantly impacted outdoor robot navigation, providing foundational techniques for terrain-aware autonomy. His achievements highlight a career dedicated to making robots more perceptive and adaptive in unstructured environments.

Research Focus

Key Achievements

4
H-Index
6
Papers
124
Total Citations
21
Avg Citations/Paper
🏆 Most Cited Paper
High resolution visual terrain classification for outdoor robots
47 citations · 2011
📈 Most Prolific Year: 2011 (3 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: University of Tübingen

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago