About

Justin Carpentier is a leading robotics researcher whose work sits at the intersection of rigid body dynamics, optimal control, and legged locomotion. He is perhaps best known as the primary architect of **Pinocchio**, an open-source C++ library for rigid body dynamics algorithms and their analytical derivatives, which has garnered over 340 citations and become a foundational tool across the robotics community. Complementing this, his development of **Crocoddyl**, a high-performance framework for multi-contact optimal control, has accumulated over 250 citations, cementing his reputation as a builder of indispensable open-source infrastructure. Carpentier's theoretical contributions are equally significant. His derivation of analytical derivatives for rigid body dynamics algorithms (133 citations) unlocked gradient-based optimization methods that were previously computationally prohibitive, directly enabling faster trajectory optimization for complex robotic systems. His work on multicontact locomotion and differential dynamic programming has advanced how legged robots navigate challenging terrains, while his pattern generator for generalized legged locomotion (114 citations) offers practical tools for humanoid and quadruped systems alike. He also contributed to the design of the TALOS humanoid robot platform, bridging hardware and algorithmic research. With his 2022 PROX-QP solver, Carpentier continues pushing numerical methods toward the reliability and speed demanded by real-world robotics applications.

Research Focus

Key Achievements

22
H-Index
63
Papers
2,123
Total Citations
34
Avg Citations/Paper
🏆 Most Cited Paper
The Pinocchio C++ library : A fast and flexible implementation of rigid body dynamics algorithms and their analytical derivatives
344 citations · 2019
📈 Most Prolific Year: 2024 (10 Papers)
🤝 Key Collaborators: 83
🏛 Institutions: Université Fédérale de Toulouse Midi-Pyrénées, Centre National de la Recherche Scientifique, Laboratoire d'Analyse et d'Architecture des Systèmes, Institut national de recherche en sciences et technologies du numérique, École Normale Supérieure, Université Paris Sciences et Lettres

Top Papers

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    257 citations
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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 33 days ago