Ludovic Righetti
École Polytechnique Fédérale de Lausanne, Max Planck Institute for Intelligent Systems, University of Southern California, New York University, Max Planck Society, École Normale Supérieure - PSL, National Research Tomsk State University, Meta (Israel), Motion Control (United States), Technische Universität Darmstadt, Supélec, Brooklyn Technical High School
Papers
112
Total Citations
4,965
H-Index
37
About
Ludovic Righetti is a prominent robotics researcher whose work spans legged locomotion, humanoid control, optimal control, and robot learning. Best known for his foundational contributions to central pattern generator (CPG)-based locomotion — demonstrated in highly cited papers on programmable CPGs for biped robots (275 citations) and sensory feedback-driven quadruped locomotion (247 citations) — Righetti has helped establish biologically inspired rhythmic control as a cornerstone methodology in legged robotics. His research on torque-controlled humanoids, including hierarchical inverse dynamics controllers for momentum regulation and balancing (254 and 143 citations), has significantly advanced the practical deployment of compliant, whole-body robot control. He also contributed to the landmark iCub platform (279 citations), one of the most influential open humanoid systems in cognitive and neuroscience research. Righetti's work on the Crocoddyl framework (257 citations) has made multi-contact optimal control dramatically more computationally accessible for the broader community. His investigations into robot learning for force control and online movement adaptation further demonstrate a commitment to enabling robots to operate safely alongside humans. With multiple papers exceeding 150 citations, Righetti's research has had enduring, cross-disciplinary impact across robotics, neuroscience, and artificial intelligence.
Research Focus
Key Achievements
Top Papers
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- 5Pattern generators with sensory feedback for the control of quadruped locomotion247 citations · 2008
- 6Online movement adaptation based on previous sensor experiences223 citations · 2011
- 7Optimal distribution of contact forces with inverse-dynamics control194 citations · 2013
- 8Learning force control policies for compliant manipulation163 citations · 2011
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