Papers

4

Total Citations

18

H-Index

3

About

Jonathan Spitz is a researcher whose work lies at the intersection of bio-inspired robotics and whole-body control for humanoid and bipedal locomotion. His primary research areas include dynamic walking, biologically inspired open-loop control using central pattern generators (CPGs), and quadratic programming (QP)-based whole-body control. Spitz’s major contributions include pioneering a trial-and-error learning framework to generate repulsors for QP-based controllers, enabling humanoid robots to better handle model inaccuracies and environmental uncertainties—a critical step toward robust real-world deployment. His work on minimal feedback to rhythm generators demonstrated how simple, bio-inspired control strategies can significantly improve a compass biped’s robustness to slope variations, bridging the gap between theoretical models and practical terrain adaptability. Additionally, Spitz explored the use of crab-walking gaits to extend the range of slopes humanoids can traverse, showcasing creative solutions to locomotion challenges. With key papers accumulating citations in the single digits—reflecting a focused, early-career impact—his research has been presented at venues like the IEEE-RAS International Conference on Humanoid Robots. Spitz’s work is notable for its emphasis on simplicity and biological inspiration, offering practical pathways for more adaptive and efficient legged robots.

Research Focus

Key Achievements

3
H-Index
4
Papers
18
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Trial-and-error learning of repulsors for humanoid QP-based whole-body control
8 citations · 2017
📈 Most Prolific Year: 2017 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Centre Inria de l'Université de Lorraine, Technion – Israel Institute of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago