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.

Check out our YouTube channel for more videos

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 - + +

References


  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