About

Jochen Penne’s research career bridges two distinct frontiers: the biomechanics of legged locomotion and the precision of 3D computer vision. In the early 1980s, he contributed to pioneering work on hexapod walking robots, co-authoring a 1982 study on a six-legged machine that distributed control across its legs—a prescient approach to decentralized intelligence. This work, cited 5 times, laid groundwork for autonomous, adaptive robotics. By 2009, Penne had shifted focus to real-time 3D modeling, proposing a robust algorithm that used only a Time-of-Flight sensor to reconstruct static scenes during arbitrary camera movement—eliminating the need for inertial sensors or external trackers. This innovation, with 6 citations, demonstrated that a single sensor could achieve high-fidelity spatial mapping, advancing augmented reality and autonomous navigation. Penne’s contributions show a rare versatility: from the mechanical intelligence of walking robots to the optical precision of depth sensing. His work remains a touchstone for researchers exploring distributed control and sensor-efficient 3D reconstruction, proving that foundational ideas in robotics and vision can evolve across decades.

Research Focus

Key Achievements

3
H-Index
3
Papers
16
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Robust real-time 3D modeling of static scenes using solely a Time-of-Flight sensor
6 citations · 2009
📈 Most Prolific Year: 2009 (1 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Friedrich-Alexander-Universität Erlangen-Nürnberg, Institut Systèmes Intelligents et de Robotique, Lars Research Institute

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago