E. Todorov

Papers

Total Citations

228

H-Index

About

E. Todorov is a pioneering researcher in robotics and control theory, best known for his groundbreaking work in whole-body model-predictive control (MPC) for humanoid robots. His key research areas span optimal control, reinforcement learning, and physics-based simulation, with a focus on enabling complex, dynamic locomotion and manipulation in legged robots. Todorov’s major contribution lies in developing computationally efficient MPC algorithms that allow humanoid robots like HRP-2 to generate stable, real-time whole-body motions—a challenge long considered the "Holy Grail" of robotics. His seminal 2015 paper on this topic has garnered over 228 citations, underscoring its impact on the field. Beyond MPC, Todorov is also celebrated for creating the MuJoCo physics simulator, a widely-used tool in robotics research that facilitates high-fidelity simulation for control and learning. His work has not only advanced theoretical understanding but also provided practical frameworks that enable robots to navigate complex environments with unprecedented agility. Todorov’s achievements have earned him recognition as a leading figure in robotics, inspiring a new generation of researchers to tackle the frontiers of autonomous motion.