Papers

4

Total Citations

375

H-Index

4

About

Thomas Fischer is a leading researcher in robotics and autonomous systems, with a primary focus on visual simultaneous localization and mapping (SLAM) and its application to mobile and legged robots. His most significant contribution is the development of S-PTAM (Stereo Parallel Tracking and Mapping), a landmark visual SLAM system that decouples real-time pose estimation from computationally intensive map building. This parallel architecture, detailed in his highly cited 2017 paper (187 citations) and its 2015 precursor (118 citations), enables robust, real-time localization for robots operating in dynamic environments. Fischer’s work is distinguished by its practical impact, extending SLAM to challenging platforms like hexapod walking robots navigating rough terrains—a problem he addressed in his 2016 study (12 citations). Beyond localization, he has advanced educational robotics, authoring a behavior-based approach (2012, 58 citations) that makes robotics accessible to students in K-12 and outreach programs. With over 375 total citations, Fischer’s research bridges theoretical innovation and real-world deployment, solidifying his reputation as a key figure in stereo vision-based autonomy.

Research Focus

Key Achievements

4
H-Index
4
Papers
375
Total Citations
94
Avg Citations/Paper
🏆 Most Cited Paper
S-PTAM: Stereo Parallel Tracking and Mapping
187 citations · 2017
📈 Most Prolific Year: 2017 (1 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: Universidad de Buenos Aires, Fundación Ciencias Exactas y Naturales

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago