Carlos Mastalli
Turing Institute, Italian Institute of Technology, Laboratoire d'Analyse et d'Architecture des Systèmes, Centre National de la Recherche Scientifique, Heriot-Watt University, University of Edinburgh, The Alan Turing Institute, Florida Institute for Human and Machine Cognition, Université Fédérale de Toulouse Midi-Pyrénées
Papers
26
Total Citations
1,035
H-Index
13
About
Carlos Mastalli is a leading robotics researcher whose work sits at the intersection of optimal control, motion planning, and legged locomotion. He is best known for creating **Crocoddyl**, an open-source framework for multi-contact optimal control that has become a foundational tool in the robotics community, accumulating over 257 citations and widely adopted for computing efficient state trajectories and control policies in complex contact scenarios. Mastalli's research has substantially advanced how legged robots—particularly quadrupeds—navigate challenging real-world terrain. His coupled planning framework for quadrupedal locomotion, integrating terrain mapping, foothold selection, and whole-body control, has garnered 140 citations, while his experimental validation of passive whole-body control on rough terrain (133 citations) demonstrated these methods in compelling physical deployments. His earlier trajectory and foothold optimization work (85 citations) helped establish low-dimensional modeling as a practical strategy for rough terrain locomotion. Beyond locomotion, Mastalli has made rigorous algorithmic contributions, advancing Differential Dynamic Programming through multi-phase contact formulations, feasibility-driven approaches, and inverse-dynamics MPC—work that improves convergence, numerical stability, and real-time applicability. Spanning humanoid design to fundamental optimal control theory, his research portfolio reflects both deep theoretical insight and strong engineering impact, making him an influential figure in modern robot motion planning and control.
Research Focus
Key Achievements
Top Papers
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- 5Differential Dynamic Programming for Multi-Phase Rigid Contact Dynamics84 citations · 2018
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- 7Inverse-Dynamics MPC via Nullspace Resolution41 citations · 2023
- 8A feasibility-driven approach to control-limited DDP39 citations · 2022
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