Hyfydy vs MuJoCo vs OpenSim

Hyfydy provides a unique combination of performance and accuracy, which is not found in other engines, such as OpenSim and MuJoCo. Here we highlight the key differences between Hyfydy, MuJoCo and OpenSim.

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Hyfydy vs MuJoCo (Summary).md

Differences between Hyfydy and MuJoCo

  • Hyfydy muscles accurately simulate tendon elasticity[1], enabling an important mechanism for energy storage-and-release in biomechanical systems[2][3]. MuJoCo does not model this phenomenon.
  • Hyfydy contact forces include realistic non-linear damping[4] and support dynamic and viscous friction coefficients. MuJoCo contacts do not model these properties.
  • Hyfydy uses error-controlled integration, which adapts the integration step size to ensure robustness and consistent simulation accuracy. MuJoCo uses fixed step size integration without error control.

Differences between Hyfydy, MuJoCo and OpenSim

  • Hyfydy uses the same muscle and contact models as OpenSimseth2019, which are well-established in biomechanics research.
  • Hyfydy and MuJoCo are similar in speed; both are orders of magnitude faster than OpenSim.
  • Hyfydy and MuJoCo both support collision detection and response between a wide range of collision primitives, compared to limited collision detection support in OpenSim.
  • MuJoCo and OpenSim are both free and open source, while Hyfydy is proprietary software.

Feature Comparison Chart

Feature Hyfydy MuJoCo OpenSim
Musculotendon dynamics + - +
Contact Models + +/- +
Collision Detection + + +/-
Accuracy / Error Control + - +
Simulation Speed + + -
Price / Open Source - + +


  1. Millard, M., Uchida, T., Seth, A., & Delp, S. L. (2013). Flexing computational muscle: modeling and simulation of musculotendon dynamics. Journal of Biomechanical Engineering, 135(2), 021005. https://doi.org/10.1115/1.4023390
  2. Blazevich, A. J., & Fletcher, J. R. (2023). More than energy cost: multiple benefits of the long Achilles tendon in human walking and running. Biological Reviews. https://doi.org/https://doi.org/10.1111/brv.13002
  3. Schumacher, P., Geijtenbeek, T., Caggiano, V., Kumar, V., & Schmitt, S. (2023). Natural and Robust Walking using Reinforcement Learning without Demonstrations in High-Dimensional Musculoskeletal Models. (August). Project page https://doi.org/10.13140/RG.2.2.33187.22569/1
  4. Hunt, K. H., & Crossley, F. R. E. (1975). Coefficient of Restitution Interpreted as Damping in Vibroimpact. Journal of Applied Mechanics, 42(2), 440. https://doi.org/10.1115/1.3423596